Micaela MORETTINI

Pubblicazioni

Micaela MORETTINI

 

95 pubblicazioni classificate nel seguente modo:

Nr. doc. Classificazioni
47 4 Contributo in Atti di Convegno (Proceeding)
45 1 Contributo su Rivista
2 2 Contributo in Volume
1 8 Tesi di dottorato
Anno
Risorse
2022
Temporal Patterns of Glucagon and Its Relationships with Glucose and Insulin following Ingestion of Different Classes of Macronutrients
NUTRIENTS
Autore/i: Gobl, C.; Morettini, M.; Salvatori, B.; Alsalim, W.; Kahleova, H.; Ahren, B.; Tura, A.
Classificazione: 1 Contributo su Rivista
Abstract: Background: glucagon secretion and inhibition should be mainly determined by glucose and insulin levels, but the relative relevance of each factor is not clarified, especially following ingestion of different macronutrients. We aimed to investigate the associations between plasma glucagon, glucose, and insulin after ingestion of single macronutrients or mixed-meal. Methods: thirty-six participants underwent four metabolic tests, based on administration of glucose, protein, fat, or mixed-meal. Glucagon, glucose, insulin, and C-peptide were measured at fasting and for 300 min following food ingestion. We analyzed relationships between time samples of glucagon, glucose, and insulin in each individual, as well as between suprabasal area-under-the-curve of the same variables (∆AUCGLUCA, ∆AUCGLU, ∆AUCINS ) over the whole participants’ cohort. Results: in individuals, time samples of glucagon and glucose were related in only 26 cases (18 direct, 8 inverse relationships), whereas relationship with insulin was more frequent (60 and 5, p < 0.0001). The frequency of significant relationships was different among tests, especially for direct relationships (p ≤ 0.006). In the whole cohort, ∆AUCGLUCA was weakly related to ∆AUCGLU (p ≤ 0.02), but not to ∆AUCINS, though basal insulin secretion emerged as possible covariate. Conclusions: glucose and insulin are not general and exclusive determinants of glucagon secretion/inhibition after mixed-meal or macronutrients ingestion.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/295010 Collegamento a IRIS

2022
Unraveling the Factors Determining Development of Type 2 Diabetes in Women With a History of Gestational Diabetes Mellitus Through Machine-Learning Techniques
FRONTIERS IN PHYSIOLOGY
Autore/i: Ilari, L.; Piersanti, A.; Gobl, C.; Burattini, L.; Kautzky-Willer, A.; Tura, A.; Morettini, M.
Classificazione: 1 Contributo su Rivista
Abstract: Gestational diabetes mellitus (GDM) is a type of diabetes that usually resolves at the end of the pregnancy but exposes to a higher risk of developing type 2 diabetes mellitus (T2DM). This study aimed to unravel the factors, among those that quantify specific metabolic processes, which determine progression to T2DM by using machine-learning techniques. Classification of women who did progress to T2DM (labeled as PROG, n = 19) vs. those who did not (labeled as NON-PROG, n = 59) progress to T2DM has been performed by using Orange software through a data analysis procedure on a generated data set including anthropometric data and a total of 34 features, extracted through mathematical modeling/methods procedures. Feature selection has been performed through decision tree algorithm and then Naïve Bayes and penalized (L2) logistic regression were used to evaluate the ability of the selected features to solve the classification problem. Performance has been evaluated in terms of area under the operating receiver characteristics (AUC), classification accuracy (CA), precision, sensitivity, specificity, and F1. Feature selection provided six features, and based on them, classification was performed as follows: AUC of 0.795, 0.831, and 0.884; CA of 0.827, 0.813, and 0.840; precision of 0.830, 0.854, and 0.834; sensitivity of 0.827, 0.813, and 0.840; specificity of 0.700, 0.821, and 0.662; and F1 of 0.828, 0.824, and 0.836 for tree algorithm, Naïve Bayes, and penalized logistic regression, respectively. Fasting glucose, age, and body mass index together with features describing insulin action and secretion may predict the development of T2DM in women with a history of GDM.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/297161 Collegamento a IRIS

2022
Estimation of Tidal Volume during Exercise Stress Test from Wearable-Device Measures of Heart Rate and Breathing Rate
APPLIED SCIENCES
Autore/i: Sbrollini, A; Catena, R; Carbonari, F; Bellini, A; Sacchetti, M; Burattini, L; Morettini, M
Classificazione: 1 Contributo su Rivista
Abstract: Tidal volume (TV), defined as the amount of air that moves in or out of the lungs with each respiratory cycle, is important in evaluating the respiratory function. Although TV can be reliably measured in laboratory settings, this information is hardly obtainable under everyday living conditions. Under such conditions, wearable devices could provide valuable support to monitor vital signs, such as heart rate (HR) and breathing rate (BR). The aim of this study was to develop a model to estimate TV from wearable-device measures of HR and BR during exercise. HR and BR were acquired through the Zephyr Bioharness 3.0 wearable device in nine subjects performing incremental cycling tests. For each subject, TV during exercise was obtained with a metabolic cart (Cosmed). A stepwise regression algorithm was used to create the model using as possible predictors HR, BR, age, and body mass index; the model was then validated using a leave-one-subject-out cross-validation procedure. The performance of the model was evaluated using the explained variance (R-2), obtaining values ranging from 0.65 to 0.72. The proposed model is a valid method for TV estimation with wearable devices and can be considered not subject-specific and not instrumentation-specific.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/304475 Collegamento a IRIS

2022
Review on Cardiorespiratory Complications after SARS-CoV-2 Infection in Young Adult Healthy Athletes
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
Autore/i: Romagnoli, S.; Sbrollini, A.; Marcantoni, I.; Morettini, M.; Burattini, L.
Classificazione: 1 Contributo su Rivista
Abstract: This review analyzes scientific data published in the first two years of the COVID-19 pandemic with the aim to report the cardiorespiratory complications observed after SARS-CoV-2 infection in young adult healthy athletes. Fifteen studies were selected using PRISMA guidelines. A total of 4725 athletes (3438 males and 1287 females) practicing 19 sports categories were included in the study. Information about symptoms was released by 4379 (93%) athletes; of them, 1433 (33%) declared to be asymptomatic, whereas the remaining 2946 (67%) reported the occurrence of symptoms with mild (1315; 45%), moderate (821; 28%), severe (1; 0%) and unknown (809; 27%) severity. The most common symptoms were anosmia (33%), ageusia (32%) and headache (30%). Cardiac magnetic resonance identified the largest number of cardiorespiratory abnormalities (15.7%). Among the confirmed inflammations, myocarditis was the most common (0.5%). In conclusion, the low degree of symptom severity and the low rate of cardiac abnormalities suggest that the risk of significant cardiorespiratory involvement after SARS-CoV-2 infection in young adult athletes is likely low; however, the long-term physiologic effects of SARS-CoV-2 infection are not established yet. Extensive cardiorespiratory screening seems excessive in most cases, and classical pre-participation cardiovascular screening may be sufficient.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/300334 Collegamento a IRIS

2022
Spectral F-wave index for automatic identification of atrial fibrillation in very short electrocardiograms
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
Autore/i: Sbrollini, A.; Marcantoni, I.; Morettini, M.; Burattini, L.
Classificazione: 1 Contributo su Rivista
Abstract: Micro as well as clinical atrial fibrillation (AF) is associated with both F-wave occurrence and high heart-rate variability (HRV). Automatic AF identification typically relies on HRV evaluation only. However, high HRV is not AF specific and may not be reliably estimated in very short electrocardiograms (ECG). This study presents a new algorithm for automatic AF identification in very short ECG based on computation of a new spectral F-wave index (SFWI). Data consisted of short (9 heartbeats) 12-lead ECG acquired from 6628 subjects divided in assessment dataset and validation dataset. Each lead was independently analyzed so that 12 values of SFWI, indicating the percentage of spectral power in the 4–10 Hz band, were obtained for each ECG. Additionally, a global SFWI value was computed as the median of SFWI distribution over leads. To identify AF, a threshold on SFWI was firstly assessed on the assessment dataset, and then evaluated on the validation dataset by computation of sensitivity (SE), specificity (SP) and accuracy (AC). Results were compared with those of standard HRV-based approaches. AF identification by SFWI was already good when considering a single lead (SE: 84.6%–88.8%, SP: 84.5%–87.0%, AC: 84.5%–87.3%), improved significantly when combining the 12 leads (SE: 89.0%, SP: 87.0%, AC: 88.7%) and, overall, performed better than standard HRV-based approaches (SE: 82.2%, SP: 83.6%, AC: 83.4%). The presented algorithm is a useful tool to automatically identify AF in very short ECG, and thus has the potentiality to be applied for detection of both micro and clinical AF.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/292667 Collegamento a IRIS

2021
Electrocardiogram-based index for the assessment of drug-induced hERG potassium channel block
JOURNAL OF ELECTROCARDIOLOGY
Autore/i: Burattini, L.; Sbrollini, A.; Scinocca, L.; Peroni, C.; Marcantoni, I.; Morettini, M.
Classificazione: 1 Contributo su Rivista
Abstract: Introduction: Drug-induced block of the hERG potassium channel could predispose to torsade de pointes, depending on occurrence of concomitant blocks of the calcium and/or sodium channels. Since the hERG potassium channel block affects cardiac repolarization, the aim of this study was to propose a new reliable index for non-invasive assessment of drug-induced hERG potassium channel block based on electrocardiographic T-wave features. Methods: ERD30% (early repolarization duration) and TS/A (down-going T-wave slope to T-wave amplitude ratio) features were measured in 22 healthy subjects who received, in different days, doses of dofetilide, ranolazine, verapamil and quinidine (all being hERG potassium channel blockers and the latter three being also blockers of calcium and/or sodium channels) while undergoing continuous electrocardiographic acquisition from which ERD30% and TS/A were evaluated in fifteen time points during the 24 h following drug administration (“ECG Effects of Ranolazine, Dofetilide, Verapamil, and Quinidine in Healthy Subjects” database by Physionet). A total of 1320 pairs of ERD30% and TS/A measurements, divided in training (50%) and testing (50%) datasets, were obtained. Drug-induced hERG potassium channel block was modelled by the regression equation BECG(%) = a·ERD30% + b·TS/A+ c·ERD30%·TS/A + d; BECG(%) values were compared to plasma-based measurements, BREF(%). Results: Regression coefficients values, obtained on the training dataset, were: a = −561.0 s−1, b = −9.7 s, c = 77.2 and d = 138.9. In the testing dataset, correlation coefficient between BECG(%) and BREF(%) was 0.67 (p < 10−81); estimation error was −11.5 ± 16.7%. Conclusion: BECG(%) is a reliable non-invasive index for the assessment of drug-induced hERG potassium channel block, independently from concomitant blocks of other ions.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/293722 Collegamento a IRIS

2021
Mathematical Model of Glucagon Kinetics for the Assessment of Insulin-Mediated Glucagon Inhibition During an Oral Glucose Tolerance Test
FRONTIERS IN ENDOCRINOLOGY
Autore/i: Morettini, Micaela; Burattini, Laura; Göbl, Christian; Pacini, Giovanni; Ahrén, Bo; Tura, Andrea
Classificazione: 1 Contributo su Rivista
Abstract: Glucagon is secreted from the pancreatic alpha cells and plays an important role in the maintenance of glucose homeostasis, by interacting with insulin. The plasma glucose levels determine whether glucagon secretion or insulin secretion is activated or inhibited. Despite its relevance, some aspects of glucagon secretion and kinetics remain unclear. To gain insight into this, we aimed to develop a mathematical model of the glucagon kinetics during an oral glucose tolerance test, which is sufficiently simple to be used in the clinical practice. The proposed model included two first-order differential equations -one describing glucagon and the other describing C-peptide in a compartment remote from plasma - and yielded a parameter of possible clinical relevance (i.e., SGLUCA(t), glucagon-inhibition sensitivity to glucose-induced insulin secretion). Model was validated on mean glucagon data derived from the scientific literature, yielding values for SGLUCA(t) ranging from -15.03 to 2.75 (ng of glucagon·nmol of C-peptide-1). A further validation on a total of 100 virtual subjects provided reliable results (mean residuals between -1.5 and 1.5 ng·L-1) and a negative significant linear correlation (r = -0.74, p < 0.0001, 95% CI: -0.82 - -0.64) between SGLUCA(t) and the ratio between the areas under the curve of suprabasal remote C-peptide and glucagon. Model reliability was also proven by the ability to capture different patterns in glucagon kinetics. In conclusion, the proposed model reliably reproduces glucagon kinetics and is characterized by sufficient simplicity to be possibly used in the clinical practice, for the estimation in the single individual of some glucagon-related parameters.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/289574 Collegamento a IRIS

2021
Enhanced adaptive matched filter for automated identification and measurement of electrocardiographic alternans
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
Autore/i: Marcantoni, I.; Sbrollini, A.; Morettini, M.; Swenne, C. A.; Burattini, L.
Classificazione: 1 Contributo su Rivista
Abstract: Electrocardiographic alternans, consisting of P-wave alternans (PWA), QRS-complex alternans (QRSA) and T-wave alternans (TWA), is an index of cardiac risk. However, only automated TWA measurement methods have been proposed so far. Here, we presented the enhanced adaptive matched filter (EAMF) method and tested its reliability in both simulated and experimental conditions. Our methodological novelty consists in the introduction of a signal enhancement procedure according to which all sections of the electrocardiogram (ECG) but the wave of interest are set to baseline, and in the extraction of the alternans area (AAr) in addition to the standard alternans amplitude (AAm). Simulated data consisted of 27 simulated ECGs representing all combinations of PWA, QRSA and TWA of low (10 μV) and high (100 μV) amplitude. Experimental data consisted of exercise 12-lead ECGs from 266 heart failure patients with an implanted cardioverter defibrillator for primary prevention. EAMF was able to accurately identify and measure all kinds of simulated alternans (absolute maximum error equal to 2%). Moreover, different alternans kinds were simultaneously present in the experimental data and EAMF was able to identify and measure all of them (AAr: 545 μV × ms, 762 μV × ms and 1382 μV × ms; AAm: 5 μV, 9 μV and 7 μV; for PWA, QRSA and TWA, respectively) and to discriminate TWA as the prevalent one (with the highest AAr). EAMF accurately identifies and measures all kinds of electrocardiographic alternans. EAMF may support determination of incremental clinical utility of PWA and QRSA with respect to TWA only.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/289895 Collegamento a IRIS

2021
Initial investigation of athletes’ electrocardiograms acquired by wearable sensors during the pre-exercise phase
THE OPEN BIOMEDICAL ENGINEERING JOURNAL
Autore/i: Romagnoli, S.; Sbrollini, A.; Colaneri, M.; Marcantoni, I.; Morettini, M.; Zitti, G.; Brocchini, M.; Pozzi, M.; Burattini, L.
Classificazione: 1 Contributo su Rivista
Abstract: Aim: The aim of this study is to support large-scale prevention programs fighting sport-related sudden cardiac death by providing a set of electrocardiographic features representing a starting point in the development of normal reference values for the pre-exercise phase. Background: In people with underlying, often unknown, cardiovascular abnormalities, increased cardiovascular load during exercise can trigger sport-related sudden cardiac death. Prevention remains the only weapon to contrast sport-related sudden cardiac death. So far, no reference values have been proposed for electrocardiograms of athletes acquired with wearable sensors in the pre-exercise phase, consisting of the few minutes immediately before the beginning of the training session. Objective: To perform an initial investigation of athletes’ electrocardiograms acquired by wearable sensors during the pre-exercise phase. Methods: The analyzed electrocardiograms, acquired through BioHarness 3.0 by Zephyr, belong to 51 athletes (Sport Database and Cycling Database of the Cardiovascular Bioengineering Lab of the Università Politecnica delle Marche, Italy). Preliminary values consist of interquartile ranges of six electrocardiographic features which are heart rate, heart-rate variability, QRS duration, ST level, QT interval, and corrected QT interval. Results: For athletes 35 years old or younger, preliminary values were [72;91]bpm, [26;47]ms, [85;104]ms, [-0.08;0.08]mm, [326;364]ms and [378;422]ms, respectively. For athletes older than 35 years old, preliminary values were [71;94]bpm, [16;65]ms, [85;100]ms, [-0.11;0.07]mm, [330;368]ms and [394;414]ms, respectively. Conclusion: Availability of preliminary reference values could help identify those athletes who, due to electrocardiographic features out of normal ranges, are more likely to develop cardiac complications that may lead to sport-related sudden cardiac death.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/291630 Collegamento a IRIS

2021
Comparison of software packages for the analysis of continuous glucose monitoring data
2021 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2021 - Conference Proceedings
Autore/i: Piersanti, A.; Giurato, F.; Burattini, L.; Tura, A.; Morettini, M.
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The use of Continuous Glucose Monitoring (CGM) systems in the management of diabetes is rapidly growing and represents an eligible technology to overcome the limitations of self-monitoring of blood glucose. However, not complete standardization of the CGM data analyses methodologies is limiting the potential of these devices. In the last few years, different software solutions have been proposed to find a common pattern for making CGM data analysis results more interpretable and reproducible. The aim of this study was to compare two of the newest open-source software packages available for CGM data analysis, GLU and iglu. To perform the comparison, CGM data of 9 subjects with type 1 diabetes coming from the open D1NAMO dataset have been analyzed with both software. Metrics available both in GLU and iglu have been compared, namely: Area Under the Curve (AUC), Time Above Range (TAR), Time Below Range (TBR), Time in Range (TIR) and Mean Absolute Deviation (MAD). Mean values for GLU and iglu were: AUC (170 ± 23 vs. 165 ± 27 mg•dl-1); TAR (40 ± 17 vs. 38 ± 21 %); TBR (6 ± 7 % in both); TIR (54 ± 18 vs. 60 ± 21 %), MAD (43 ± 20 vs. 67 ± 28 mg•dl-1). Only MAD was found statistically different between GLU and iglu. In conclusion, this comparison provided an overview of the graphical and computational aspects in CGM analysis provided by GLU and iglu software packages, which could be useful to researchers and clinicians to find a transparent and consistent way of interpreting CGM data.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/291910 Collegamento a IRIS

2021
Repeated Structuring & Learning Procedure for Detection of Myocardial Ischemia: a Robustness Analysis
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Autore/i: Sbrollini, A.; Marcantoni, I.; Morettini, M.; Swenne, C. A.; Burattini, L.
Editore: NLM (Medline)
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Myocardial ischemia, consisting in a reduction of blood flow to the heart, may cause sudden cardiac death by myocardial infarction or trigger serious abnormal rhythms. Thus, its timely identification is crucial. The Repeated Structuring and Learning Procedure (RS&LP), an innovative constructive algorithm able to dynamically create neural networks (NN) alternating structuring and learning phases, was previously found potentially useful for myocardial ischemia detection. However, performance of created NN depends on three parameters, the values of which need to be set a priori by the user: maximal number of layers (NL), maximal number of initializations (NI) and maximal number of confirmations (NC). A robustness analysis of RS&LP to varying values of NL, NI and NC is fundamental for clinical applications concerning myocardial ischemia detection but was never performed before; thus, it was the aim the present study. Thirteen serial ECG features were extracted by pairs of ECGs belonging to 84 cases (patients with induced myocardial ischemia) and 398 controls (patients with no myocardial ischemia) and used as inputs to learn (50% of population) and test (50% of population) NNs with varying values of NL (1,2,3,4,10), NI (50,250,500,1000,1500) and NC (2,5,10,20,50). Performance of obtained NNs was compared in terms of area under the curve (AUC) of the receiver operating characteristics. Overall, 13 NNs were considered; 12 (92%) were characterized by AUC≥80% and 4 (31%) by AUC≥85%. Thus, RS&LP proved to be robust when creating NNs for detecting of myocardial ischemia.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/294844 Collegamento a IRIS

2021
Hepatic and extrahepatic insulin clearance in mice with double deletion of glucagon-like peptide-1 and glucose-dependent insulinotropic polypeptide receptors
BIOMEDICINES
Autore/i: Morettini, M.; Piersanti, A.; Burattini, L.; Pacini, G.; Gobl, C.; Ahren, B.; Tura, A.
Classificazione: 1 Contributo su Rivista
Abstract: The aim of this study was to investigate whether incretins, at physiological levels, affect hepatic and/or extrahepatic insulin clearance. Hepatic and extrahepatic insulin clearance was studied in 31 double incretin receptor knockout (DIRKO) and 45 wild-type (WT) mice, which underwent an Intravenous Glucose Tolerance Test (IVGTT). A novel methodology based on mathematical modeling was designed to provide two sets of values (FEL-P1, CLP-P1; FEL-P2, CLP-P2 ) accounting for hepatic and extrahepatic clearance in the IVGTT first and second phases, respectively, plus the respective total clearances, CLT-P1 and CLT-P2 . A statistically significant difference between DIRKO and WT was found in CLT-P1 (0.61 [0.48–0.82] vs. 0.51 [0.46–0.65] (median [interquartile range]); p = 0.02), which was reflected in the peripheral component, CLP-P1 (0.18 [0.13–0.27] vs. 0.15 [0.11–0.22]; p = 0.04), but not in the hepatic component, FEL-P1 (29.7 [26.7–34.9] vs. 28.9 [25.7–32.0]; p = 0.18). No difference was detected between DIRKO and WT in CLT-P2 (1.38 [1.13–1.75] vs. 1.69 [1.48–1.87]; p = 0.10), neither in CLP-P2 (0.72 [0.64–0.81] vs. 0.79 [0.69–0.87]; p = 0.27) nor in FEL-P2 (37.8 [35.1–43.1] vs. 39.8 [35.8–44.2]; p = 0.46). In conclusion, our findings suggest that the higher insulin clearance observed in DIRKO compared with WT during the IVGTT first phase may be due to its extrahepatic component.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/291634 Collegamento a IRIS

2021
Signal Processing for Athletic Cardiovascular Monitoring with Wearable Sensors: Fully Automatic Detection of Training Phases from Heart Rate Data
Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021
Autore/i: Romagnoli, S.; Sbrollini, A.; Scalese, A.; Marcantoni, I.; Morettini, M.; Burattini, L.
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Heart rate (HR) recording is a non-invasive, cheap and time-efficient tool for continuous cardiovascular monitoring through wearable technologies in sport applications directly on field. Although, HR measures cannot inform equally on all aspects of cardiac responses to training, given the individual HR kinetic that depends on internal and external influencing factors. Knowledge of the training context is required to correctly compute and interpret HR-derived indices. Training context is characterized by the training phases, their distribution and training load. The aim of this study is to develop an algorithm for automatic detection of training phases in HR series to boost signal processing for athletic cardiovascular monitoring with wearable technologies. The algorithm computes the start and end times of the training phases. It exploits the variance of HR series computed over moving overlapping windows to detect automatically training transition phases. The algorithm was tested on HR series acquired during middle distance running and jogging. The algorithm showed promising results: mean errors were globally lower than 5 s and percentage error did not exceed 5%. Thus, the fully automatic algorithm for detection of training phases can boost HR signal processing for reliable computation and interpretation of HR-derived indices during continuous cardiovascular monitoring with wearable sensors in athletes.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/296401 Collegamento a IRIS

2021
A Preliminary Validation of a New Surgical Procedure for the Treatment of Primary Bladder Neck Obstruction Using a Computational Modeling Approach
BIOENGINEERING
Autore/i: Serpilli, Michele; Zitti, Gianluca; Dellabella, Marco; Castellani, Daniele; Maranesi, Elvira; Morettini, Micaela; Lenci, Stefano; Burattini, Laura
Classificazione: 1 Contributo su Rivista
Abstract: A new surgical procedure for the treatment of primary bladder neck obstruction with maintenance of anterograde ejaculation is proposed. In place of monolateral or bilateral bladder neck incision, associated with a loss of ejaculation rate of up to 30%, the new surgical procedure consists of laser drilling the bladder neck with a number of holes and without muscle fiber disrup- tion. The effect of this novel procedure has been studied numerically, with a simplified two-dimen- sional numerical model of the internal urethral sphincter, varying the position and the number of holes in the fibrotic region of the urethral tissue. Results show an improvement of the urethral sphincter opening by increasing the number of holes, ranging from about 6% to 16% of recovery. Moreover, a non-aligned position of holes positively influences the opening recovery. The concen- trations of maximum principal strain and stress have been registered in the proximity of the inter- face between the physiologic and diseased sphincter, and in those regions where the radial thick- ness is significantly thinner. The effects on the first five patients have been included in the study, showing improvement in micturition, lower urinary tract symptoms, sustained ejaculatory func- tion, and quality of life.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/290912 Collegamento a IRIS

2021
Model-Based Assessment of Hepatic and Extrahepatic Insulin Clearance from Short Insulin-Modified IVGTT in Women with a History of Gestational Diabetes
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Autore/i: Piersanti, A.; Abdul Rahman, N. H. B.; Gobl, C.; Burattini, L.; Kautzky-Willer, A.; Pacini, G.; Tura, A.; Morettini, M.
Editore: NLM (Medline)
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Insulin clearance is an integral component of insulin metabolism. Yet, little is known about separate contribution of hepatic and extrahepatic insulin clearance in type 2 diabetes and in high-risk populations, such as women who experienced gestational diabetes mellitus (pGDM). A model-based method was recently proposed to assess both contributions from 3-hour insulin-modified intravenous glucose tolerance test (IM-IVGTT); the aim of this study was to assess the reliability of short (1 hour) IM-IVGTT in the application of such model-based method and to evaluate the role of the two contributions in determining insulin clearance in pGDM. A total of 115 pGDM women and 41 who remained healthy during pregnancy (CNT) were analyzed early postpartum and underwent a 3-hour IMIVGTT. Peripheral insulin clearance (CLP), hepatic fractional extraction (FEL) and extrahepatic distribution volume (VP) were estimated by performing a best-fit procedure on insulin IMIVGTT data considering firstly the overall 3-hour duration and then limiting data to 1 hour. Results showed no significant difference in parameter values between the 3-hour and the 1-hour IM-IVGTT. Comparison between pGDM and CNT (1-hour) showed no significant difference in CLp (0.23 [0.29] vs. 0.27 [0.43] L·min-1; p=0.64), FEL (50.2 [15.1] vs. 50.9 [11.7] %; p=0.63) and VP (2.01 [2.99] vs. 2.70 [4.00] L; p=0.92). In conclusion, short IM-IVGTT provides a reliable assessment of hepatic and extrahepatic insulin clearance through such model-based method. Its application to the study of pGDM women showed no alteration in hepatic and extrahepatic contributions with respect to women who had a healthy pregnancy.Clinical Relevance- This study proves the reliability of short (1 hour) IM-IVGTT to assess hepatic and extrahepatic insulin clearance in women who experienced gestational diabetes.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/294845 Collegamento a IRIS

2021
Cardiac Electrical Alternans in Pregnancy: An Observational Study
Computing in Cardiology
Autore/i: Marcantoni, I.; Assogna, R.; Sbrollini, A.; Morettini, M.; Burattini, L.
Editore: IEEE Computer Society
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: In pregnancy, if the woman has a cardiovascular disease, her fetus has an increased risk of inherited cardiac genetic disorders. Aim of this study was to evaluate electrocardiographic alternans (ECGA, mu V) of 23 pregnant women, comparing 12 mothers of fetuses with normal rhythm (MumNRF) and 11 mothers of arrhythmic fetuses (MumArrF). ECGA is a noninvasive cardiac electrical risk marker able to reveal heart electrical instability. ECGA manifests in the ECG as P-wave alternans (PWA), QRS alternans (QRSA) and/or T-wave alternans (TWA). Analysis was performed by the enhanced adaptive matched filter method. ECGA distributions were expressed as: median (interquartile range). Comparisons were performed by the Wilcoxon rank-sum test. Although showing similar heart rate (MumNRF: 85 (19) bpm; MumArrF: 90 (13) bpm), ECGA was higher in MumArrF population than MumNRF one (PWA: 9 (7) mu V vs. 14 (14) mu V; QRSA: 9 (10) mu V vs. 17 (16) mu V, TWA: 12 (14) mu Vvs. 28(17) mu V), but only TWA distributions were statistically different. Moreover, TWA was higher than in a female healthy population (on average 18mu V)in 70% of MumArrF, vs. 33% of MumNRF. Thus, higher TWA in our MumArrF seems to reflect a more unstable heart electrical condition of arrhythmic fetuses' mothers than normal-rhythm fetuses' mothers.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/295901 Collegamento a IRIS

2021
Ensemble empirical mode decomposition for efficient r-peak detection in electrocardiograms acquired by portable sensors during sport activity
2021 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2021 - Conference Proceedings
Autore/i: Romagnoli, S.; Marcantoni, I.; Campanella, K.; Sbrollini, A.; Morettini, M.; Burattini, L.
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Wearable and portable electrocardiographic devices are revolutionizing athlete's screening through digital health application enabling a continuous monitoring of important cardiac parameters in real-time. Automatic examination of electrocardiogram (ECG) acquired during sport activity is challenging because acquisition conditions often lead to record ECGs with low signal to noise ratio (SNR). The initial issue of automatic ECG analysis is the identification of R peaks. R peaks are fundamental for the estimation of heart rate, which is the primary clinical parameter used by athletes for athletic performance evaluation. Thus, the aim of this research is to propose an R-peak detection algorithm for ECGs acquired during sport activity by portable and wearable sensors dealing with low SNR. The algorithm is based on a noise assisted data analysis method: Ensemble Empirical Mode Decomposition method (EEMD). Localization of R peaks is primarily performed on the first intrinsic mode function extracted by the EEMD. The algorithm was tested on 'Run on indoor treadmill' dataset from Physionet. ECGs were acquired during running/light jogging on an indoor treadmill and present a low SNR (1±7 dB). The developed EEMD-based algorithm showed good performances in terms of positive predicted value (91.08%), sensitivity (92.76%), false discovery rate (8.92), false negative rate (7.24%), cumulative statistical index (83.84%) and mean R-peak position error 1.10 [0.46;1.46]ms. EEMD-based algorithm performs efficiently also in computing heart rate. In conclusion, the developed R-peak detection EEMD-based algorithm showed good level of performances even working on low-SNR ECG acquired during sport activity by portable sensors.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/291911 Collegamento a IRIS

2021
An innovative training based on robotics for older people with subacute stroke: study protocol for a randomized controlled trial
TRIALS
Autore/i: Maranesi, E.; Bevilacqua, R.; Di Rosa, M.; Pelliccioni, G.; Di Donna, V.; Luzi, R.; Morettini, M.; Sbrollini, A.; Casoni, E.; Rinaldi, N.; Baldoni, R.; Lattanzio, F.; Burattini, L.; Riccardi, G. R.
Classificazione: 1 Contributo su Rivista
Abstract: Background: Stroke is a leading cause of disability, injury, and death in elderly people and represents a major public health problem with substantial medical and economic consequences. The incidence of stroke rapidly increases with age, doubling for each decade after age 55 years. Gait impairment is one of the most important problems after stroke, and improving walking function is often a key component of any rehabilitation program. To achieve this goal, a robotic gait trainer seems to be promising. In fact, some studies underline the efficacy of robotic gait training based on end-effector technology, for different diseases, in particular in stroke patients. In this randomized controlled trial, we verify the efficacy of the robotic treatment in terms of improving the gait and reducing the risk of falling and its long-term effects. Methods: In this single-blind randomized controlled trial, we will include 152 elderly subacute stroke patients divided in two groups to receive a traditional rehabilitation program or a robotic rehabilitation using G-EO system, an end-effector device for the gait rehabilitation, in addition to the traditional therapy. Twenty treatment sessions will be conducted, divided into 3 training sessions per week, for 7 weeks. The control group will perform traditional therapy sessions lasting 50 min. The technological intervention group, using the G-EO system, will carry out 30 min of traditional therapy and 20 min of treatment with a robotic system. The primary outcome of the study is the evaluation of the falling risk. Secondary outcomes are the assessment of the gait improvements and the fear of falling. Further evaluations, such as length and asymmetry of the step, walking and functional status, and acceptance of the technology, will be carried. Discussion: The final goal of the present study is to propose a new approach and an innovative therapeutic plan in the post-stroke rehabilitation, focused on the use of a robotic device, in order to obtain the beneficial effects of this treatment. Trial registration: ClinicalTrials.gov NCT04087083. Registered on September 12, 2019
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/290829 Collegamento a IRIS

2021
Adaptive bradycardia assessment in preterm infants
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
Autore/i: Sbrollini, A.; Mancinelli, M.; Marcantoni, I.; Morettini, M.; Carnielli, V. P.; Burattini, L.
Classificazione: 1 Contributo su Rivista
Abstract: In preterm infants, bradycardias associate to critical health conditions. Standard algorithm for bradycardia identification assumes baseline heart rate (BHR) equal to 150bpm and identifies bradycardias when heart rate (HR) decreases below 100bpm. Since preterm infants show BHR varying from 120bpm to 160bpm, a new adaptive algorithm for real-time bradycardia identification was presented. The adaptive algorithm continuously adjusts BHR by averaging HR over the preceding 10-minute window after eliminating out-of-range HR values, and identifies bradycardias when HR decreases below 67% of BHR. Both standard and adaptive algorithms were evaluated using long-term (20.3–70.3h) electrocardiographic recordings of ten preterm infants (“Preterm Infant Cardio-respiratory Signals” database by Physionet). Bradycardias were characterized in terms of rate (BR, h−1) and depth (BD, bpm). Being also indexes of infants’ health conditions, gestational age at birth (GA, days), birth weight (BW, kg) and HR were used to evaluate performances of the algorithms. Association between BR and BD vs GA, BW and HR was evaluated by computation of the correlation coefficient (ρ). Overall, standard and adaptive algorithms identified 516 and 546 bradycardias, respectively; median BR and BD values were comparable (1.25h−1 and 76bpm vs 1.26h−1 and 70bpm, respectively). However, the adaptive algorithm provided higher BD for HR>150bpm, and vice versa. Significant (p value<0.05) correlations were found between BR and HR (ρ=0.69), BR and BW (ρ=−0.76), and BR and HR (ρ=0.76) only when using the adaptive algorithm. Thus, the adaptive algorithm is superior to the standard algorithm and represents a potentially clinically useful tool for real-time bradycardia assessment in preterm infants.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/290831 Collegamento a IRIS

2021
An integrated lumped-parameter model of the cardiovascular system for the simulation of acute ischemic stroke: description of instantaneous changes in hemodynamics
MATHEMATICAL BIOSCIENCES AND ENGINEERING
Autore/i: Civilla, L.; Sbrollini, A.; Burattini, L.; Morettini, M.
Classificazione: 1 Contributo su Rivista
Abstract: Acute Ischemic Stroke (AIS) is defined as the acute condition of occlusion of a cerebral artery and is often caused by a Hypertensive Condition (HC). Due to its sudden occurrence, AIS is not observable the right moment it occurs, thus information about instantaneous changes in hemodynamics is limited. This study aimed to propose an integrated Lumped Parameter (LP) model of the cardiovascular system to simulate an AIS and describe instantaneous changes in hemodynamics. In the integrated LP model of the cardiovascular system, heart chambers have been modelled with elastance systems with controlled pressure inputs; heart valves have been modelled with static open/closed pressure-controlled valves; eventually, the vasculature has been modelled with resistor-inductor-capacitor (RLC) direct circuits and have been linked to the rest of the system through a series connection. After simulating physiological conditions, HC has been simulated by changing pressure inputs and constant RLC parameters. Then, AIS occurring in arteries of different sizes have been simulated by considering time-dependent RLC parameters due to the elimination from the model of the occluding artery; instantaneous changes in hemodynamics have been evaluated by Systemic Arteriolar Flow (Qa) and Systemic Arteriolar Pressure (Pa) drop with respect to those measured in HC. Occlusion of arteries of different sizes leaded to an average Qa drop of 0.38 ml/s per cardiac cycle (with minimum and maximum values of 0.04 ml/s and 1.93 ml/s) and average Pa drop of 0.39 mmHg, (with minimum and maximum values of 0.04 mmHg and 1.98 mmHg). In conclusion, hemodynamic variations due to AIS are very small with respect to HC. A direct relation between the inverse of the length of the artery in which the occlusion occurs and the hemodynamic variations has been highlighted; this may allow to link the severity of AIS to the length of the interested artery.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/290662 Collegamento a IRIS

2020
Extended segmented beat modulation method for cardiac beat classification and electrocardiogram denoising
ELECTRONICS
Autore/i: Nasim, A.; Sbrollini, A.; Morettini, M.; Burattini, L.
Classificazione: 1 Contributo su Rivista
Abstract: Beat classification and denoising are two challenging and fundamental operations when processing digital electrocardiograms (ECG). This paper proposes the extended segmented beat modulation method (ESBMM) as a tool for automatic beat classification and ECG denoising. ESBMM includes four main steps: (1) beat identification and segmentation into PQRS and TU segments; (2) wavelet-based time-frequency feature extraction; (3) convolutional neural network-based classification to discriminate among normal (N), supraventricular (S), and ventricular (V) beats; and (4) a template-based denoising procedure. ESBMM was tested using the MIT–BIH arrhythmia database available at Physionet. Overall, the classification accuracy was 91.5% while the positive predictive values were 92.8%, 95.6%, and 83.6%, for N, S, and V classes, respectively. The signal-to-noise ratio improvement after filtering was between 0.15 dB and 2.66 dB, with a median value equal to 0.99 dB, which is significantly higher than 0 (p < 0.05). Thus, ESBMM proved to be a reliable tool to classify cardiac beats into N, S, and V classes and to denoise ECG tracings.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/283394 Collegamento a IRIS

2020
T-Wave Alternans in Nonpathological Preterm Infants
ANNALS OF NONINVASIVE ELECTROCARDIOLOGY
Autore/i: Marcantoni, I.; Sbrollini, A.; Agostinelli, G.; Surace, F. C.; Colaneri, M.; Morettini, M.; Pozzi, M.; Burattini, L.
Classificazione: 1 Contributo su Rivista
Abstract: Background: Sudden infant death syndrome is more frequent in preterm infants (PTI) than term infants and may be due to cardiac repolarization instability, which may manifest as T-wave alternans (TWA) on the electrocardiogram (ECG). Therefore, the aim of the present work was to analyze TWA in nonpathological PTI and to open an issue on its physiological interpretation. Methods: Clinical population consisted of ten nonpathological PTI (gestational age ranging from 293/7 to 342/7 weeks; birth weight ranging from 0.84 to 2.10 kg) from whom ECG recordings were obtained (“Preterm infant cardio-respiratory signals database” by Physionet). TWA was identified through the heart-rate adapting match filter method and characterized in terms of mean amplitude values (TWAA). TWA correlation with several other clinical and ECG features, among which gestational age–birth weight ratio, RR interval, heart-rate variability, and QT interval, was also performed. Results: TWA was variable among infants (TWAA = 26 ± 11 µV). Significant correlations were found between TWAA versus birth weight (ρ = −0.72, p =.02), TWAA versus gestational age–birth weight ratio (ρ = 0.76, p =.02) and TWAA versus heart-rate variability (ρ = −0.71, p =.02). Conclusions: Our preliminary retrospective study suggests that nonpathological PTI show TWA of few tens of µV, the interpretation of which is still an open issue but could indicate a condition of cardiac risk possibly related to the low development status of the infant. Further investigations are needed to solve this issue.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/273413 Collegamento a IRIS

2020
AdvFPCG-Delineator: Advanced delineator for fetal phonocardiography
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
Autore/i: Tomassini, S.; Sbrollini, A.; Strazza, A.; Sameni, R.; Marcantoni, I.; Morettini, M.; Burattini, L.
Classificazione: 1 Contributo su Rivista
Abstract: Fetal phonocardiogram (FPCG) consists in the recording of fetal heart sounds by means of a sensor placed on the mother's abdominal surface. Usually, FPCG includes two major sounds for each fetal cardiac cycle: S1, produced by the sudden closure of mitral and tricuspid valves, and S2 produced by the closure of aortic and pulmonary valves. The aim of the present study was to propose AdvFPCG-Delineator for automatic fetal S1 and S2 identification and to demonstrate its reliability in different clinical conditions. The method consists of a wavelet-based filtering procedure followed by the computation of the scalogram, from which S1 and S2 were identified using a threshold-based algorithm. AdvFPCG-Delineator was tested on the “Simulated Fetal PCGs database” (37 FPCG signals) and on the experimental “Shiraz University fetal heart sounds database” (119 FPCG signals), both available at PhysioNet (https://physionet.org). Manual S1 and S2 annotations and simultaneously acquired cardiotocographic recordings were used to compute reference fetal heart rate (FHR) for the simulated and experimental databases, respectively. No statistically significant difference was observed between estimated vs reference FHR (140 bpm vs 140 bpm, respectively) for the simulated database, for which AdvFPCG-Delineator was also able to track beat-to-beat variability (correlation over 92%). Additionally, no statistically significant difference was observed between estimated vs reference FHR (141 bpm vs 140 bpm, respectively) for the experimental database, even when stratifying by clinical conditions (maternal age, gestational age, etc.). In conclusion, AdvFPCG-Delineator proved to be a reliable method to automatically identify S1 and S2 from fetal phonocardiograms.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/282806 Collegamento a IRIS

2020
Annotation dataset of the cardiotocographic recordings constituting the “CTU-CHB intra-partum CTG database”
DATA IN BRIEF
Autore/i: Romagnoli, S.; Sbrollini, A.; Burattini, L.; Marcantoni, I.; Morettini, M.; Burattini, L.
Classificazione: 1 Contributo su Rivista
Abstract: The proposed dataset provides annotations for the 552 cardiotocographic (CTG) recordings included in the publicly available “CTU-CHB intra-partum CTG database” from Physionet (https://physionet.org/content/ctu-uhb-ctgdb/1.0.0/). Each CTG recording is composed by two simultaneously acquired signals: i) the fetal heart rate (FHR) and ii) the maternal tocogram (representing uterine activity). Annotations consist in the detection of starting and ending points of specific CTG events on both FHR signal and maternal tocogram. Annotated events for the FHR signal are the bradycardia, tachycardia, acceleration and deceleration episodes. Annotated events for the maternal tocogram are the uterine contractions. The dataset also reports classification of each deceleration as early, late, variable or prolonged, in relation to the presence of a uterine contraction. Annotations were obtained by an expert gynecologist with the support of CTG Analyzer, a dedicated software application for automatic analysis of digital CTG recordings. These annotations can be useful in the development, testing and comparison of algorithms for the automatic analysis of digital CTG recordings, which can make CTG interpretation more objective and independent from clinician's experience.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/281117 Collegamento a IRIS

2020
Insulin clearance is altered in women with a history of gestational diabetes progressing to type 2 diabetes
NMCD. NUTRITION METABOLISM AND CARDIOVASCULAR DISEASES
Autore/i: Tura, A.; Gobl, C.; Morettini, M.; Burattini, L.; Kautzky-Willer, A.; Pacini, G.
Classificazione: 1 Contributo su Rivista
Abstract: Background and aims: Insulin clearance is a relevant process in glucose homeostasis. In this observational study, we aimed to assess insulin clearance (ClINS) in women with former gestational diabetes (fGDM) both early after delivery and after a follow-up. Methods and results: We analysed 59 fGDM women, and 16 women not developing GDM (CNT). All women underwent an oral glucose tolerance test (OGTT) yearly, and an insulin-modified intravenous glucose tolerance test (IVGTT) at baseline and at follow-up end (until 7 years). Both IVGTT and OGTT ClINS was assessed as insulin secretion to plasma insulin ratio. We also defined IVGTT first (0–10 min) and second phase (10–180 min) ClINS. We found that 14 fGDM women progressed to type 2 diabetes (PROG), whereas 45 women remained diabetes-free (NONPROG). At baseline, IVGTT ClINS showed alterations in PROG, especially in second phase (0.88 ± 0.10 l·min−1 in PROG, 0.60 ± 0.06 in NONPROG, 0.54 ± 0.07 in CNT, p ≤ 0.03). Differences in ClINS were not found from OGTT. Cox regression analysis showed second phase ClINS as significant type 2 diabetes predictor (hazard ratio = 1.90, 95% confidence interval 1.09–3.30, p = 0.02). Conclusion: This study showed that insulin clearance derived from an insulin-modified IVGTT is notably altered in women with history of GDM progressing towards type 2 diabetes.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/282420 Collegamento a IRIS

2020
Early temporal prediction of Type 2 Diabetes Risk Condition from a General Practitioner Electronic Health Record: A Multiple Instance Boosting Approach
ARTIFICIAL INTELLIGENCE IN MEDICINE
Autore/i: Bernardini, M.; Morettini, M.; Romeo, L.; Frontoni, E.; Burattini, L.
Classificazione: 1 Contributo su Rivista
Abstract: Early prediction of target patients at high risk of developing Type 2 diabetes (T2D) plays a significant role in preventing the onset of overt disease and its associated comorbidities. Although fundamental in early phases of T2D natural history, insulin resistance is not usually quantified by General Practitioners (GPs). Triglyceride-glucose (TyG) index has been proven useful in clinical studies for quantifying insulin resistance and for the early identification of individuals at T2D risk but still not applied by GPs for diagnostic purposes. The aim of this study is to propose a multiple instance learning boosting algorithm (MIL-Boost) for creating a predictive model capable of early prediction of worsening insulin resistance (low vs high T2D risk) in terms of TyG index. The MIL-Boost is applied to past electronic health record (EHR) patients’ information stored by a single GP. The proposed MIL-Boost algorithm proved to be effective in dealing with this task, by performing better than the other state-of-the-art ML competitors (Recall from 0.70 and up to 0.83). The proposed MIL-based approach is able to extract hidden patterns from past EHR temporal data, even not directly exploiting triglycerides and glucose measurements. The major advantages of our method can be found in its ability to model the temporal evolution of longitudinal EHR data while dealing with small sample size and variability in the observations (e.g., a small variable number of prescriptions for non-hospitalized patients). The proposed algorithm may represent the main core of a clinical decision support system.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/280099 Collegamento a IRIS

2020
Artificial neural network for atrial fibrillation identification in portable devices
SENSORS
Autore/i: Marinucci, D.; Sbrollini, A.; Marcantoni, I.; Morettini, M.; Swenne, C. A.; Burattini, L.
Classificazione: 1 Contributo su Rivista
Abstract: Atrial fibrillation (AF) is a common cardiac disorder that can cause severe complications. AF diagnosis is typically based on the electrocardiogram (ECG) evaluation in hospitals or in clinical facilities. The aim of the present work is to propose a new artificial neural network for reliable AF identification in ECGs acquired through portable devices. A supervised fully connected artificial neural network (RSL_ANN), receiving 19 ECG features (11 morphological, 4 on F waves and 4 on heart-rate variability (HRV)) in input and discriminating between AF and non-AF classes in output, was created using the repeated structuring and learning (RSL) procedure. RSL_ANN was created and tested on 8028 (training: 4493; validation: 1125; testing: 2410) annotated ECGs belonging to the “AF Classification from a Short Single Lead ECG Recording” database and acquired with the portable KARDIA device by AliveCor. RSL_ANN performance was evaluated in terms of area under the curve (AUC) and confidence intervals (CIs) of the received operating characteristic. RSL_ANN performance was very good and very similar in training, validation and testing datasets. AUC was 91.1% (CI: 89.1%–93.0%), 90.2% (CI: 86.2%–94.3%) and 90.8% (CI: 88.1%–93.5%) for the training, validation and testing datasets, respectively. Thus, RSL_ANN is a promising tool for reliable identification of AF in ECGs acquired by portable devices.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/282883 Collegamento a IRIS

2020
COVID-19 in Italy: Dataset of the Italian Civil Protection Department
DATA IN BRIEF
Autore/i: Italian Civil Protection, Department; Morettini, M.; Sbrollini, A.; Marcantoni, I.; Burattini, L.
Classificazione: 1 Contributo su Rivista
Abstract: The database here described contains data of integrated surveillance for the “Coronavirus disease 2019” (abbreviated as COVID-19 by the World Health Organization) in Italy, caused by the novel coronavirus SARS-CoV-2. The database, included in a main folder called COVID-19, has been designed and created by the Italian Civil Protection Department, which currently manages it. The database consists of six folders called ‘aree’ (containing charts of geographical areas interested by containment measures), ‘dati-andamento-nazionale’ (containing data relating to the national trend of SARS-CoV-2 spread), ‘dati-json’ (containing data that summarize the national, provincial and regional trends of SARS-CoV-2 spread), ‘dati-province’ (containing data relating to the provincial trend of SARS-CoV-2 spread), ‘dati-regioni’ (containing data relating to the regional trend of SARS-CoV-2 spread) and ‘schede-riepilogative’ (containing summary sheets relating to the provincial and regional trends of SARS-CoV-2 spread). The Italian Civil Protection Department daily receives data by the Italian Ministry of Health, analyzes them and updates the database. Thus, the database is subject to daily updates and integrations. The database is freely accessible (CC-BY-4.0 license) at https://github.com/pcm-dpc/COVID-19. This database is useful to provide insight on the spread mechanism of SARS-CoV-2, to support organizations in the evaluation of the efficiency of current prevention and control measures, and to support governments in the future prevention decisions.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/277055 Collegamento a IRIS

2020
Electrocardiographic Alternans in Myocardial Bridge: A Case Report
Computing in Cardiology
Autore/i: Marcantoni, I.; Di Menna, A.; Rossini, F.; Turco, F.; Morettini, M.; Sbrollini, A.; Bianco, F.; Pozzi, M.; Burattini, L.
Editore: IEEE Computer Society
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Myocardial bridge (MB) is a congenital heart condition in which a 'bridge' of myocardium is overlying a 'tunneled' coronary artery. MB can be associated with a series of critical cardiac events. Aim of this study was to evaluate electrocardiographic alternans (ECGA) on a MB patient, being ECGA a cardiac electrical risk index defined as beat-to-beat alternation of electrocardiographic P-wave, QRS-complex and T-wave morphology at stable heart rate. ECGA analysis was performed in a 1-hour 12-lead electrocardiographic recording of a 54 years-old MB male patient at rest by application of the heart-rate adaptive match filter method. Areas of P-wave, QRS and T-wave alternans (PWAA, QRSAA, TWAA) were measured, evaluating also the prevalent among the three. Results showed the prevalent alternans was T-wave alternans, being TWAA on average equal to 6.3 µV×s (PWAA=4.7 µV×s, QRSAA=4.3 µV×s); TWAA prevalence occurrence rate was 94% (PWAA: 5%, QRSAA:1%). TWAA was also found to be significantly correlated (p=0.72, p<10-2) with heart rate. Eventually, TWAA was at least twice higher than in previously analyzed male healthy subjects. Thus, MB seems to be associated to a higher cardiac electrical risk, possibly especially while performing physical activity at high heart rate.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/288230 Collegamento a IRIS

2020
Model-Based Estimation of Electrocardiographic QT Interval from Phonocardiographic Heart Sounds in Healthy Subjects
Computing in Cardiology
Autore/i: Sbrollini, A.; Morettini, M.; Marcantoni, I.; Burattini, L.
Editore: IEEE Computer Society
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The electrocardiographic QT interval is an index of cardiac risk commonly used in clinics. Accurate QT measure is challenging, especially in noisy conditions, when acquisitions of phonocardiograms (PCGs) may be more reliable than acquisitions of electrocardiograms (ECGs). However, PCG features are less used in clinics. Thus, aim of the study was to propose a model for indirectly measuring the electrocardiographic QT interval from the phonocardiographic heart sounds in healthy subjects. To this aim, simultaneously acquired PCGs and ECGs of 99 healthy subjects were processed to obtain median PCG and ECG beats. Beat length, S1 onset and S2 onset were identified from the median PCG beat, while QT interval (QT) was measured from the median ECG beat. Then, a regression model was formulated by regression analysis to obtain PCG-based QT estimation (QT) and validated by leave-one-out cross-validation. Correlation coefficient (p) and estimation error were also computed. QT and QT did not differ significantly (model formulation: 362ms vs 358ms; model validation:360ms vs 358ms, respectively; P>0.5) and were significantly correlated (model formulation: p=0.7, p<10-13; model validation: p=0.6, P<10-10); median error is 1 ms (<0.5 in %). Thus, the proposed model provides a reliable estimation of QT interval from PCG heart sounds in healthy subjects.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/288228 Collegamento a IRIS

2019
Glucose effectiveness and its components in relation to body mass index
EUROPEAN JOURNAL OF CLINICAL INVESTIGATION
Autore/i: Morettini, M.; Di Nardo, F.; Ingrillini, Laura; Fioretti, S.; Gobl, C.; Kautzky-Willer, A.; Tura, Andrea; Pacini, Giovanni; Burattini, L.
Classificazione: 1 Contributo su Rivista
Abstract: Background: Obesity is known to induce a deterioration of insulin sensitivity (SI), one of the insulin-dependent components of glucose tolerance. However, few studies investigated whether obesity affects also the insulin-independent component, that is glucose effectiveness (SG). This cross-sectional study aimed to analyse SG and its components in different body mass index (BMI) categories. Materials and methods: Three groups of subjects spanning different BMI (kg m−2) categories underwent a 3-h frequently sampled intravenous glucose tolerance test: Lean (LE; 18.5 ≤ BMI < 25, n = 73), Overweight (OW; 25 ≤ BMI < 30, n = 90), and Obese (OB; BMI ≥ 30, n = 41). OB has been further divided into two subgroups, namely Obese I (OB-I; 30 ≤ BMI < 35, n = 27) and Morbidly Obese (OB-M; BMI ≥ 35, n = 14). Minimal model analysis provided SG and its components at zero (GEZI) and at basal (BIE) insulin. Results: Values for SG were 1.98 ± 1.30 × 10−2·min−1 in all subjects grouped and 2.38 ± 1.23, 1.84 ± 0.82, 1.59 ± 0.61 10−2·min−1 in LE, OW and OB, respectively. In all subjects grouped, a significant inverse linear correlation was found between the log-transformed values of SG and BMI (r = −0.3, P < 0.0001). SG was significantly reduced in OW and OB with respect to LE (P < 0.001) but no significant difference was detected between OB and OW (P = 0.35) and between OB-I and OB-M (P = 0.25). Similar results were found for GEZI. BIE was not significantly different among NW, OW and OB (P = 0.11) and between OB-I and OB-M (P ≥ 0.07). Conclusions: SG and its major component GEZI deteriorate in overweight individuals compared to those in the normal BMI range, without further deterioration when BMI increases above 30 kg m−2.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/267129 Collegamento a IRIS

2019
Classification of drug-induced hERG potassium-channel block from electrocardiographic T-wave features using artificial neural networks
ANNALS OF NONINVASIVE ELECTROCARDIOLOGY
Autore/i: Morettini, M.; Peroni, C.; Sbrollini, A.; Marcantoni, I.; Burattini, L.
Classificazione: 1 Contributo su Rivista
Abstract: Background: Human ether‐à‐go‐go‐related gene (hERG) potassium‐channel block represents a harmful side effect of drug therapy that may cause torsade de pointes (TdP). Analysis of ventricular repolarization through electrocardiographic T‐wave features represents a noninvasive way to accurately evaluate the TdP risk in drug‐safety studies. This study proposes an artificial neural network (ANN) for noninvasive electrocardiography‐ based classification of the hERG potassium‐channel block. Methods: The data were taken from the “ECG Effects of Ranolazine, Dofetilide, Verapamil, and Quinidine in Healthy Subjects” Physionet database; they consisted of median vector magnitude (VM) beats of 22 healthy subjects receiving a single 500 μg dose of dofetilide. Fourteen VM beats were considered for each subject, relative to time‐points ranging from 0.5 hr before to 14.0 hr after dofetilide administration. For each VM, changes in two indexes accounting for the early and the late phases of repolarization, ΔERD30% and ΔTS/A, respectively, were computed as difference between values at each postdose time‐point and the predose time‐point. Thus, the dataset contained 286 ΔERD30%‐ΔTS/A pairs, partitioned into training, validation, and test sets (114, 29, and 143 pairs, respectively) and used as inputs of a two‐layer feedforward ANN with two target classes: high block (HB) and low block (LB). Optimal ANN (OANN) was identified using the training and validation sets and tested on the test set. Results: Test set area under the receiver operating characteristic was 0.91; sensitivity, specificity, accuracy, and precision were 0.93, 0.83, 0.92, and 0.96, respectively. Conclusion: OANN represents a reliable tool for noninvasive assessment of the hERG potassium‐channel block.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/271789 Collegamento a IRIS

2019
TyG-er: An ensemble Regression Forest approach for identification of clinical factors related to insulin resistance condition using Electronic Health Records
COMPUTERS IN BIOLOGY AND MEDICINE
Autore/i: Bernardini, M.; Morettini, M.; Romeo, L.; Frontoni, E.; Burattini, L.
Classificazione: 1 Contributo su Rivista
Abstract: Insulin resistance is an early-stage deterioration of Type 2 diabetes. Identification and quantification of insulin resistance requires specific blood tests; however, the triglyceride-glucose (TyG) index can provide a surrogate assessment from routine Electronic Health Record (EHR) data. Since insulin resistance is a multi-factorial condition, to improve its characterisation, this study aims to discover non-trivial clinical factors in EHR data to determine where the insulin-resistance condition is encoded.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/269259 Collegamento a IRIS

2019
A dataset for the development and optimization of fall detection algorithms based on wearable sensors
DATA IN BRIEF
Autore/i: Cotechini, Valentina; Belli, Alberto; Palma, Lorenzo; Morettini, Micaela; Burattini, Laura; Pierleoni, Paola
Classificazione: 1 Contributo su Rivista
Abstract: This paper describes a dataset acquired on 8 subjects while simulating 13 types of falls and 5 types of Activities of Daily Living (ADL), each repeated 3 times. In details, data includes 4 simulated falls forward (falling on knees ending up lying, ending in lateral position, ending up lying, ending up lying with recovery), 4 backward (falling sitting ending up lying, ending in lateral position, ending up lying, ending up lying with recovery), 2 lateral right (ending up lying, ending up lying with recovery), 2 lateral left (ending up lying, ending up lying with recovery), and 1 syncope. Simulated ADL are: lying on a bed then standing; walking a few meters; sitting on a chair then standing; go up or down three steps; and standing after picking something. Data were acquired using a MARG sensor, a wearable multisensory device tied to the subject's waist, that recorded time-variations of the subject's acceleration and orientation (expressed through the yaw, pitch and roll angles). These data can be useful in the development and test of algorithms to automatically identify and classify fall events. Fall detection systems are particularly useful when a subject is alone and not able to stand up after a fall, since an automatic alarm can be sent remotely to receive proper help.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/264666 Collegamento a IRIS

2019
Digital cardiotocography: What is the optimal sampling frequency?
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
Autore/i: Romagnoli, Sofia; Sbrollini, Agnese; Burattini, Luca; Marcantoni, Ilaria; Morettini, Micaela; Burattini, Laura
Classificazione: 1 Contributo su Rivista
Abstract: Cardiotocography (CTG) is the most popular prenatal diagnostic test for establishing fetal health and consists in simultaneous recording of fetal heart rate (FHR, bpm) and maternal uterine contraction (UC, mmHg) traces. Typically, FHR and UC traces are visually analyzed and interpreted by clinicians. Recently, software applications like CTG Analyzer have been developed to support visual CTG interpretation by making it more objective and independent from clinician’s experience. Automatic CTG analysis requires CTG-traces digitalization and thus assessment of a correct sampling frequency (SF). Thus, this paper aims to investigate dependency of automatic CTG analysis on SF in order to identify optimal SF (OSF) for FHR and UC traces that minimizes computational efforts without jeopardizing CTG interpretation. To this aim, the “CTU-CHB intra-partum CTG database” was considered and visually annotated by an expert gynecologist. FHR and UC traces, originally sampled at 4 Hz, were down sampled at 2 Hz, 1 Hz, 0.4 Hz and 0.2 Hz, and automatically analyzed using CTG Analyzer. Eventually, results obtained through automatic analysis were compared to visual annotations, which were taken as reference. A cumulative statistical index (CSI), ranging from 0.00% to 100.00%, was defined as a linear combination of positive-predictive value, sensitivity, false-positive rate and false-negative rate. OSF was defined as the one that maximizes CSI. If CSI was showing the same value for more than one SF, the lowest SF was selected as the optimal since minimizing computational efforts. Results indicate that OSF for FHR is 2 Hz (CSI ≥ 85.41%), whereas OSF for UC is 0.2 Hz (CSI = 75.21%).
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/264306 Collegamento a IRIS

2019
Glucose Effectiveness from Short Insulin-Modified IVGTT and Its Application to the Study of Women with Previous Gestational Diabetes Mellitus
DIABETES & METABOLISM JOURNAL
Autore/i: Morettini, M.; Castriota, C.; Gobl, C.; Kautzky-Willer, A.; Pacini, G.; Burattini, L.; Tura, A.
Classificazione: 1 Contributo su Rivista
Abstract: Background: This study aimed to design a simple surrogate marker (i.e., predictor) of the minimal model glucose effectiveness (SG), namely calculated SG (CSG), from a short insulin-modified intravenous glucose tolerance test (IM-IVGTT), and then to apply it to study women with previous gestational diabetes mellitus (pGDM). Methods: CSG was designed using the stepwise model selection approach on a population of subjects (n=181) ranging from normal tolerance to type 2 diabetes mellitus (T2DM). CSG was then tested on a population of women with pGDM (n=57). Each subject underwent a 3-hour IM-IVGTT; women with pGDM were observed early postpartum and after a follow-up period of up to 7 years and classified as progressors (PROG) or non-progressors (NONPROG) to T2DM. The minimal model analysis provided a reference SG. Results: CSG was described as CSG=1.06×10-2+5.71×10-2×KG/Gpeak, KG being the mean slope (absolute value) of loge glucose in 10-25- A nd 25-50-minute intervals, and Gpeak being the maximum of the glucose curve. Good agreement between CSG and SG in the general population and in the pGDM group, both at baseline and follow-up (even in PROG and NONPROG subgroups), was shown by the Bland-Altman plots (<5% observations outside limits of agreement), and by the test for equivalence (equivalence margin not higher than one standard deviation). At baseline, the PROG subgroup showed significantly lower SG and CSG values compared to the NONPROG subgroup (P<0.03). Conclusion: CSG is a valid SG predictor. In the pGDM group, glucose effectiveness appeared to be impaired in women progressing to T2DM.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/277943 Collegamento a IRIS

2019
Compressed Segmented Beat Modulation Method using Discrete Cosine Transform
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Autore/i: Nasim, A.; Sbrollini, A.; Marcantoni, I.; Morettini, M.; Burattini, L.
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Currently used 24-hour electrocardiogram (ECG) monitors have been shown to skip detecting arrhythmias that may not occur frequently or during standardized ECG test. Hence, online ECG processing and wearable sensing applications have been becoming increasingly popular in the past few years to solve a continuous and long-term ECG monitoring problem. With the increase in the usage of online platforms and wearable devices, there arises a need for increased storage capacity to store and transmit lengthy ECG recordings, offline and over the cloud for continuous monitoring by clinicians. In this work, a discrete cosine transform (DCT) compressed segmented beat modulation method (SBMM) is proposed and its applicability in case of ambulatory ECG monitoring is tested using Massachusetts Institute of Technology-Beth Israel Deaconess Medical Center (MIT-BIH) ECG Compression Test Database containing Holter tape normal sinus rhythm ECG recordings. The method is evaluated using signal-to-noise (SNR) and compression ratio (CR) considering varying levels of signal energy in the reconstructed ECG signal. For denoising, an average SNR of 4.56 dB was achieved representing an average overall decline of 1.68 dBs (37.9%) as compared to the uncompressed signal processing while 95 % of signal energy is intact and quantized at 6 bits for signal storage (CR=2) compared to the original 12 bits, hence resulting in 50% reduction in storage size.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/273186 Collegamento a IRIS

2019
Wavelet filtering of fetal phonocardiography: A comparative analysis
MATHEMATICAL BIOSCIENCES AND ENGINEERING
Autore/i: Tomassini, S.; Strazza, A.; Sbrollini, A.; Marcantoni, I.; Morettini, M.; Fioretti, S.; Burattini, L.
Classificazione: 1 Contributo su Rivista
Abstract: Fetal heart rate (FHR) monitoring can serve as a benchmark to identify high-risk fetuses. Fetal phonocardiogram (FPCG) is the recording of the fetal heart sounds (FHS) by means of a small acoustic sensor placed on maternal abdomen. Being heavily contaminated by noise, FPCG processing implies mandatory filtering to make FPCG clinically usable. Aim of the present study was to perform a comparative analysis of filters based on Wavelet transform (WT) characterized by different combinations of mothers Wavelet and thresholding settings. By combining three mothers Wavelet (4th-order Coiflet, 4th-order Daubechies and 8th-order Symlet), two thresholding rules (Soft and Hard) and three thresholding algorithms (Universal, Rigorous and Minimax), 18 different WT-based filters were obtained and applied to 37 simulated and 119 experimental FPCG data (PhysioNet/PhysioBank). Filters performance was evaluated in terms of reliability in FHR estimation from filtered FPCG and noise reduction quantified by the signal-to-noise ratio (SNR). The filter obtained by combining the 4th-order Coiflet mother Wavelet with the Soft thresholding rule and the Universal thresholding algorithm was found to be optimal in both simulated and experimental FPCG data, since able to maintain FHR with respect to reference (138.7[137.7; 140.8] bpm vs. 140.2[139.7; 140.7] bpm, P > 0.05, in simulated FPCG data; 139.6[113.4; 144.2] bpm vs. 140.5[135.2; 146.3] bpm, P > 0.05, in experimental FPCG data) while strongly incrementing SNR (25.9[20.4; 31.3] dB vs. 0.7[−0.2; 2.9] dB, P < 10-14, in simulated FPCG data; 22.9[20.1; 25.7] dB vs. 15.6[13.8; 16.7] dB, P < 10-37, in experimental FPCG data). In conclusion, the WT-based filter obtained combining the 4th-order Coiflet mother Wavelet with the thresholding settings constituted by the Soft rule and the Universal algorithm provides the optimal WT-based filter for FPCG filtering according to evaluation criteria based on both noise and clinical features.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/269344 Collegamento a IRIS

2019
Fifty Years of Biomedical Engineering: From Origin to Smart Technologies
The First Outstanding 50 Years of "Università Politecnica delle Marche"
Autore/i: Burattini, Laura; Di Nardo, Francesco; Morettini, Micaela; Verdini, Federica; Fioretti, Sandro
Classificazione: 2 Contributo in Volume
Abstract: In Italy, the Bioengineering Community was founded in 1980. The kick-off meeting was held in Montesicuro, a little village near Ancona and organized by Prof. Tommaso Leo from the then-named “Università degli Studi di Ancona” (now Università Politecnica delle Marche, UNIVPM) in cooperation with the nascent National Group of Bioengineering. This chapter aims to produce a brief review of the main results in Biomedical Engineering by UNIVPM during the first 50 years useful to understand the present and to track future contributions for the next 50 years. It is also an occasion to recall the pioneering work on the Bioengineering of the Neuromuscular, Cardiovascular and Metabolic systems performed by our leading colleagues Tommaso Leo, Paolo Mancini and Roberto Burattini, as well as to describe significant research achievements obtained by professors, researchers, post-doc fellows and PhD students who worked and/or are currently working at the UNVPM. Though mainly focusing on research findings in the above cited physiological systems, it is also worth mentioning in this chapter that UNIVPM has also an educational mission, provided by the two Biomedical Engineering courses currently active at the Engineering Faculty: the three-year Bachelor and the two-year Master (in English) courses.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/278101 Collegamento a IRIS

2019
Self-Monitoring of Cardiac Risk while Running Around Ancona
2019 IEEE 23rd International Symposium on Consumer Technologies, ISCT 2019
Autore/i: Sbrollini, A.; Caraceni, G.; Nasim, A.; Marcantoni, I.; Morettini, M.; Belli, A.; Pierleoni, P.; Burattini, L.
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Running is the most common physical activity. Being an aerobic activity, it can act as a trigger for critical cardiac events that may degenerate in sport-related sudden cardiac death. Nowadays, smartphone applications combined with wearable sensors are typically used to monitor runner's performance during training, but almost never to evaluate their cardiac risk conditions. Thus, aim of this study was to propose CaRiSMA as a useful Android application for self-monitoring of cardiac activity of runners while wearing a cardiac sensor and running by strictly following a route around the city of Ancona (6.1 Km). Cardiac data from 10 young runners were recorded and transferred to a smartphone to be analyzed by CaRiSMA, an Android application that provides two traffic lights as output, relative to cardiac health status of the runner and correctness of training intensity. The first traffic light was green in all cases but one for which it was yellow, indicating no risk and increased risk conditions, respectively. The second traffic light was yellow in all cases, suggesting a reduction of the training intensity. In conclusion, CaRiSMA demonstrated to be a potentially useful Android application for self-monitoring of cardiac activity of runners while wearing a cardiac sensor.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/272430 Collegamento a IRIS

2019
Electrocardiogram-Derived Respiratory Signal in Sleep Apnea by Segmented Beat Modulation Method
2019 IEEE 23rd International Symposium on Consumer Technologies, ISCT 2019
Autore/i: Sbrollini, A.; Marcantoni, I.; Nasim, A.; Morettini, M.; Burattini, L.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The most common sleep disorder is sleep apnea, whose manifestations are long breathing pauses. Sleep apnea assessment is usually performed by polysomnography. During this long-term monitoring, patient respiration and other biosignals are recorded by many sensors, causing a high level of discomfort. Thus, methods able to indirectly estimate the biosignal of interest from the others measured should be preferred. Respiration indirectly measured from electrocardiogram (ECG) is called ECG-derived respiratory (EDR) signal. Recently, Segmented Beat Modulation Method (SBMM) was proposed as a good method for EDR signal estimation in normal breathing. Thus, the aim of this study was to assess the quality of EDR signal estimation by SBMM in pathological events of sleep apnea. With this purpose, sixteen long term polysomnographic recordings from MITBIH Polysomnographic Database were considered. After standard preprocessing, respiration and ECG signals were divided in 30s windows and, in order to match to provided annotations, each window was classified into Normal or Apnea. EDR signal was estimated by SBMM procedure from each ECG window. Respiration and EDR signals were then processed by Fourier analysis to extract respiration frequencies. Respiration frequencies computed from respiration and EDR signals were compared in term of error. Results confirmed the good quality of the estimated EDR signal. Respiration frequency extracted from EDR signal in both Normal (16[13;19]cpm) and Apnea windows (18[15;21]cpm) are equal to those extracted from respiration signal (Normal: 16 [13;19]cpm and Apnea: 18 [15;21]cpm), providing null error distributions. In conclusion, SBMM proved to be a promising tool for EDR signal estimation.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/272432 Collegamento a IRIS

2019
Extraction of digital cardiotocographic signals from digital cardiotocographic images: Robustness of eCTG procedure
ELECTRONICS
Autore/i: Sbrollini, A.; Brini, L.; Di Tillo, M.; Marcantoni, I.; Morettini, M.; Burattini, L.
Classificazione: 1 Contributo su Rivista
Abstract: A recently developed software application, eCTG, extracts cardiotocographic (CTG) signals from digital CTG images, possibly obtained by scanning paper CTG reports. The aim of this study was to evaluate eCTG robustness across varying image formats, resolution and screw. Using 552 digital CTG signals from the “CTU-UHB Intrapartum Cardiotocography Database” of Physionet, seven sets of digital CTG images were created, differing in format (.TIFF, .PNG and .JPEG), resolution(96 dpi, 300 dpi and 600 dpi) and screw (0.0◦, 0.5◦, and 1.0◦). All created images were submitted to eCTG for CTG signals extraction. Quality of extracted signals was statistically evaluated based 1) on signal morphology, by computation of the correlation coefficient (ρ) and of the mean signal error percent (MSE%), and 2) on signal clinical content, by assessment of 18 standard CTG variables.For all sets of images, ρ was high (ρ ≥ 0.81) and MSE% was small (MSE% ≤ 2%). However, significant changes occurred in median values of four, four and five standard CTG variables in image sets with 96 dpi resolution, 0.5◦ screw and 1.0◦ screw, respectively. In conclusion, for an optimal eCTG performance, digital images should be saved in lossless formats, have a resolution of at least 300 dpi and not be affected by screw.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/271089 Collegamento a IRIS

2019
Bradycardia Assessment in Preterm Infants
IFMBE Proceedings
Autore/i: Sbrollini, A.; Mancinelli, M.; Marcantoni, I.; Morettini, M.; Burattini, L.
Editore: Springer
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Prematurity is a severe condition, usually correlated with critical outcomes. One of the major diseases in preterm infants is bradycardia, defined as the heart rate decreasing under 100 bpm for at least two heartbeats in duration. Usually, bradycardia is considered as a manifestation of immature cardiorespiratory control, but no studies investigated its nature in relation to the different clinical features of preterm infants. Thus, aim of this work is to assess the relation between bradycardia features and the main preterm infant clinical features, weight and gestational age. Ten preterm infants were considered, classified according with three criteria: the weight classification, the gestational age classification and the birth size assessment (that combined the two previous classifications). For each preterm infant, bradycardias are automatically identified and characterized in term of bradycardia features: amplitude, duration and area. Moreover, bradycardia events are classified according with their severity. Finally, bradycardia feature distributions of classes that belong to the same classification criterion were compared. Results seems suggesting that bradycardia features differences are more relevant in preterm infants with different weights than in those with different gestational age, contrary to what expected. Anyway, the best results in term of classification were obtained in the birth size assessment; thus, a combined approach that considers both weight and gestational age is preferable. Moreover, a combined evaluation of amplitude and duration for bradycardia characterization can better assess the severity of this arrhythmia and of the preterm infant clinical status.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/272504 Collegamento a IRIS

2019
Sport Database: Cardiorespiratory data acquired through wearable sensors while practicing sports
DATA IN BRIEF
Autore/i: Sbrollini, A.; Morettini, M.; Maranesi, E.; Marcantoni, I.; Nasim, A.; Bevilacqua, R.; Riccardi, G. R.; Burattini, L.
Classificazione: 1 Contributo su Rivista
Abstract: Sport Database is a collection of 126 cardiorespiratory data, acquired through wearable sensors from 81 subjects while practicing 10 different sports. Each cardiorespiratory dataset consists of demographic info (gender, age, weight, height, smoking habit, alcohol consumption and weekly training rate), cardiorespiratory signals (electrocardiogram, heart-rate series, RR-interval series and breathing-rate series) and training notes. Demographic info was collected by survey. Cardiorespiratory signals were acquired through the chest strap BioHarness 3.0 by Zephyr. Eventually, training notes including the sport-dependent training protocol, were manually annotated. Sport Database may be useful to support: 1) the investigation of cardiorespiratory system adaptations to different types of physical exercise; 2) the development of automatic algorithms finalized to real-time health monitoring of athletes and preventive identification of subjects at increased risk of sport-related sudden cardiac death; and, 3) clinical testing of the BioHarness 3.0 by Zephyr. Further acquisitions could involve other sports, other cardiovascular signals and/or parameters, data from different biological systems, and other acquisition devices.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/272255 Collegamento a IRIS

2019
Recurrence Quantification Analysis for Motion Artifacts in Wearable ECG Sensors
2019 IEEE 23rd International Symposium on Consumer Technologies, ISCT 2019
Autore/i: Nasim, A.; Marcantoni, I.; Sbrollini, A.; Morettini, M.; Burattini, L.
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Recurrence quantification analysis (RQA) allows the measurement of signal's regular and chaotic states using recurrence plots instead of deriving information purely from visual analysis. The current study presents RQA of multiple ECG time series simultaneously recorded through different electrodes and depicts the effect of motion artifacts through electrode synchronization and non-synchronization. The ECG data is acquired from a healthy 25-year-old male performing different exercise activities such as standing, walking and jumping. Also, the electrode in every recorded signal is placed at angle offset of 0°, 45° and 90°. The RQA analysis measures recurrence rate (RR), line entropy (ENT) and average diagonal length (L) reveal a highly stable and least chaotic signal in case of standing (RR=0.73, ENT=4.94, L=106.12), somewhat stable and a bit chaotic in case of walking (RR=0.75, ENT=5.35, L=129.13) and least stable and most chaotic in case of subject performing a jump (RR=0.61, ENT=5.07, L=99.16). Secondly, highest and second highest disturbances with respect to exercise movements are observed for electrode combinations (3, 4) and (1, 4). Distinguishing values for RQA-based measures for different exercise movements suggest that RQA is a powerful tool for differentiation of regular and irregular states occurring due to motion artifacts in the temporal patterns of ECG.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/272428 Collegamento a IRIS

2019
PCG-Decompositor: A New Method for Fetal Phonocardiogram Filtering Based on Wavelet Transform Multi-level Decomposition
IFMBE Proceedings
Autore/i: Strazza, A.; Sbrollini, A.; Olivastrelli, M.; Piersanti, A.; Tomassini, S.; Marcantoni, I.; Morettini, M.; Fioretti, S.; Burattini, L.
Editore: Springer
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Fetal phonocardiography (FPCG) is a non-invasive acoustic recording of fetal heart sounds (fHS). The fHS auscultation plays an important diagnostic role in assessing fetal wellbeing. Typically, FPCG is a non-stationary signal corrupted by the presence of noise. Thus, high-amplitude noise makes detection of FPCG waveforms challenging. Thus, appropriate filtering procedures have to be applied in order to make FPCG clinically usable. In the recent years, Wavelet transformation (WT) filtering has been proposed. In particular, aim of this study is to propose a new method based on WT multi-level decomposition filtering: PCG-Decompositor. To this aim, PCG-Decompositor based on Coiflets mother Wavelet (4th order, 9 levels of decomposition) was applied to 119 real FPCG tracings, all available in Physionet. PCG-Decompositor is a dependent thresholding technique based on FPCG multi-level decomposition analysis. Performances of PCG-Decompositor are computed against soft-thresholding denoising technique (STDT) in terms of Root Mean Square Error (RMSE) and fetal heart rate (fHR). In terms of fHR, PCG-Decompositor and STDT are compared between themselves and also with the so-called annotations, given by the average fHR using a simultaneous cardiotocography analysis. Original signal to noise ratio (SNR) values ranged from 7.1 dB to 24.4 dB; after application of PCG-Decompositor, SNR increased significantly, ranging from 9.7 dB to 26.9 dB (P < 10−7). Moreover, PCG-Decompositor showed a lower dispersion than STDT (RMSE: 0.7 dB vs. 1.2 dB), introduced no FPCG signal delay and left fHR unaltered. Thus, PCG-Decompositor could be a suitable and robust technique to denoise FPCG signals.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/272507 Collegamento a IRIS

2019
Recurrence Analysis of Human Body Movements during Activities of Daily Living
2019 IEEE 23rd International Symposium on Consumer Technologies, ISCT 2019
Autore/i: Nasim, A.; Morettini, M.; Marcantoni, I.; Sbrollini, A.; Burattini, L.
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Recurrence quantification analysis (RQA) is used to differentiate and analyze the regular and irregular parts of a time-series signal using recurrence plots and quantification measures. This work presents RQA for human body movements during routine activities of daily life (ADL) using parameters recorded using a wearable sensor attached to the test subjects waist. The current research uses data from 8 subjects performing 5 different daily life activities, lying and stand, pick and stand, sitting and stand, step up and down, and walking. Simulating the RQA plots for activity and non-activity phases for squared vector magnitude parameter for each of the record we quantify the level of signal stability and disruption in terms of RQA analysis measures recurrence rate (RR), determinism (DET) and line entropy (ENT). The RQA parameters reveal a chaotic behavior in case of activity (RR=0.249, DET=0.510, ENT=0.732), and a stable or least chaotic behavior in case of non-activity (RR=0.466, DET=0.726, ENT=1.205) regions of time. Distinguishing values for RQA-based measures for different human body movements taking place during daily life activities might be used for human activity monitoring, fall detection for elderly and body movement modelling and analysis alaorithms.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/272431 Collegamento a IRIS

2019
Electrocardiographic Alternans: A New Approach
IFMBE Proceedings
Autore/i: Marcantoni, I.; Calabrese, D.; Chiriatti, G.; Melchionda, R.; Pambianco, B.; Rafaiani, G.; Scardecchia, E.; Sbrollini, A.; Morettini, M.; Burattini, L.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Alternans is an electrophysiological phenomenon consisting in a beat-to-beat variation of the morphology of an electrocardiographic (ECG) waveform. Literature has particularly studied T-wave alternans (TWA) because it has been widely recognized as a noninvasive and clinically useful index to predict occurrence of malignant ventricular arrhythmias and, eventually, sudden cardiac death. Historically, alternans of other segments of ECG, like P wave (PWA), or QRS complex (QRSA) gained less interest than TWA, but this is an incomplete vision of the action potential (AP). AP is influenced by electrical activity of all myocardial cells, so it is reasonable that all ECG waveforms could be affected by alternans phenomenon. ECG alternans (ECGA) can be intended as the prevalent nature of alternans. This study aimed to use the heart-rate adaptive match filter (AMF) method, previously applied for TWA applications, to detect ECGA. AMF effectiveness was tested on simulated alternating ECG (alternans-amplitude range: 10 µV–200 µV), characterized by single- and multiple-wave alternans (always of the same amplitude and morphology). AMF method proved to be specific, being able to recognize ECGA absence, and particularly sensitive to TWA. In general, in case of singular-wave alternans, AMF correctly identified the type of alternans and correctly determined its amplitude (mean error: 0%). When TWA was combined to PWA or QRSA, only TWA was identified with an overestimation of its amplitude (mean error: 23%). In conclusion, overall AMF proved its effectiveness and specificity in revealing and discriminating ECGA.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/272508 Collegamento a IRIS

2019
TWA Identifier for Cardiac Risk Self-Monitoring during Hemodialysis: A Case Report
2019 IEEE 23rd International Symposium on Consumer Technologies, ISCT 2019
Autore/i: Leoni, C.; Marcantoni, I.; Sbrollini, A.; Morettini, M.; Burattini, L.
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Rate of sudden cardiac death (SCD) is increased in hemodialysis (HD) patients. Cardiac risk can be evaluated in terms of electrocardiographic (ECG) T-wave alternans (TWA). Aim of the present study was to propose TWA Identifier as a software application for cardiac risk self-monitoring based on the TWA index, and to test it on a patient while performing a HD session. TWA Identifier can be installed on any portable device and may analyze real-time ECG data acquired by wearable sensors. Core of TWA Identifier is the well-established heart-rate adaptive match filter method for TWA identification. TWA Identifier quantified TWA from a continuous 24-hours ECG acquired using a wearable Holter ECG recorder in a HD patient during a HD day. The recording was divided into macro-time periods, one prior, one contemporary and two following the HD session. On average, TWA values were higher than normal, ranged from 35 μV to 78 μV, and were particularly high during the HD session, while decreased afterwards. Thus, the HD patient was at increased SCD risk, especially during the treatment. In conclusion, TWA Identifier represents a useful tool for real-time cardiac risk self-monitoring during HD.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/272429 Collegamento a IRIS

2019
Insulin clearance in women with a history of gestational diabetes assessed by mathematical model analyses of intravenous glucose tolerance test
IFMBE Proceedings
Autore/i: Morettini, M.; Gobl, C.; Kautzky-Willer, A.; Pacini, G.; Tura, A.; Burattini, L.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Circulating concentrations of insulin are determined by a balance between the secretion rate of insulin from pancreatic beta-cells and insulin degradation (“clearance”). However, limited attention has been devoted to the study of insulin clearance in women with former gestational diabetes mellitus (GDM), which are known to be at increased type 2 diabetes risk. The aim of this study was to provide a detailed analysis of insulin clearance in women with former GDM. A population of 156 white Caucasian women, was analyzed early postpartum (4–6 months after delivery) and classified in two groups: women with previous GDM (pGDM, n = 115) and women that remain healthy during pregnancy (CNT, n = 41). All women underwent a 3-hour Insulin-Modified Intravenous Glucose Tolerance Test (IM-IVGTT). Insulin clearance temporal patterns were derived by mathematical modelling of IM-IVGTT data; average insulin clearance values were also considered during the whole test, and in the first - (0–10 min) and second phase (10–180 min). Insulin clearance temporal patterns were found to be different between CNT and pGDM group (p < 0.0001). Average insulin clearance was found different over the second phase of the test (p = 0.04), being equal to 0.54 [0.41] and 0.59 [0.41] l·min−1 in CNT and pGDM group, respectively. In conclusion, some abnormalities in former GDM women, compared to a group of healthy women were detected. This may be of relevance for more accurate estimation of type 2 diabetes risk.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/272506 Collegamento a IRIS

2019
Dofetilide-Induced Microvolt T-Wave Alternans
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Autore/i: Marcantoni, I.; Laratta, R.; Mascia, G.; Ricciardi, L.; Sbrollini, A.; Nasim, A.; Morettini, M.; Burattini, L.
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Dofetilide is an antiarrhythmic drug that selectively inhibits the rapid component of the delayed rectifier potassium current. The administration of dofetilide may cause ventricular arrhythmias and torsade de pointes. Electrocardiographic (ECG) microvolt T-wave alternans (TWA), an electrophysiologic phenomenon consisting in the beat-to-beat alternation of the T-wave amplitude requiring computerized algorithms to be detected, has also been associated to malignant ventricular arrhythmias. Aim of the present study was to evaluate if dofetilide induces TWA during the 24 hours following administration. The study population consisted of 22 healthy subjects ("ECG Effects of Ranolazine, Dofetilide, Verapamil, and Quinidine in Healthy Subjects" database by Physionet) to whom a 500 μg-dose of dofetilide was administered. For each subject, 10 s ECG were acquired at baseline (0.5 hour before dofetilide administration) and at 15 time points during the 24 hours following the drug administration. ECG were then processed for automatic TWA detection by correlation method. In 21 subjects out of 22, after dofetilide administration, TWA significantly increased to a peak value (median TWA values went from 6 μV at baseline to a max 32 μV; p<0.05), on average after 5 hours, to then come back to values closer to baseline. Thus, in healthy subjects, dofetilide increases occurrence and levels (6 times baseline value on average) of TWA in the hours following its administration.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/273187 Collegamento a IRIS

2019
Former gestational diabetes: Mathematical modeling of intravenous glucose tolerance test for the assessment of insulin clearance and its determinants
MATHEMATICAL BIOSCIENCES AND ENGINEERING
Autore/i: Morettini, Micaela; Göbl, Christian; Kautzky-Willer, Alexandra; Pacini, Giovanni; Tura, Andrea; Burattini, Laura
Classificazione: 1 Contributo su Rivista
Abstract: Women with a previous history of gestational diabetes mellitus (GDM) have increased risk of developing GDM in future pregnancies (i.e. recurrent GDM) and also Type 2 Diabetes (T2D). Insulin clearance represents one of the processes regulating glucose tolerance but has been scarcely investigated for its possible impairment in high-risk subjects. The aim of this study was to identify possible determinants of insulin clearance in women with a previous history of GDM. A detailed model-based analysis of a regular 3-hour, insulin-modified intravenous glucose tolerance test (IM-IVGTT) has been performed in women with a previous history of GDM (pGDM, n = 115) and in women who had a healthy pregnancy (CNT, n = 41) to assess total, first-phase and second-phase insulin clearance (ClINS-TOT, ClINS-FP and ClINS-SP) and other metabolic parameters (insulin sensitivity SI, glucose effectiveness SG, beta-cell function and disposition index DI). CLINS-SP was found increased in pGDM with respect to CNT and was found significantly inversely linearly correlated with SG (r = -0.20, p = 0.03, slope: -16.2, 95% CI -30.9 to -1.4, intercept: 1.1, 95% CI 0.7-1.4) and also with DI (r = -0.22, p = 0.02, slope: -10.0, 95% CI -18.5 to -1.6, intercept: 0.9, 95% CI 0.7-1.3). Disposition index, accounting for the combined contribution of insulin sensitivity and beta-cell function, and glucose effectiveness were identified as possible determinants of insulin clearance in women with a previous history of GDM. This may be of relevance for more accurate estimation and prevention of the risk for recurrent GDM and T2D.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/272776 Collegamento a IRIS

2019
Simultaneously acquired data from contactless and wearable devices for direct and indirect heart-rate measurement
DATA IN BRIEF
Autore/i: Pierleoni, P.; Gambi, E.; Ricciuti, M.; Sbrollini, A.; Palma, L.; Belli, A.; Morettini, M.; Burattini, L.
Classificazione: 1 Contributo su Rivista
Abstract: The proposed dataset provides a complete set of simultaneously acquired data from contactless and wearable devices for direct and indirect heart-rate measurement. Data were acquired on a total of 20 healthy white Caucasian subjects wearing no makeup (10 males and 10 females; age: 22.50 ± 1.57 years; height: 173 ± 10 cm; weight: 62.80 ± 9.52 kg) and consisted of: i) videos of the subject's face acquired by a RGB-D (Red, Green, Blue and Depth) camera (Microsoft Kinect v2), which is a contactless device; ii) electrocardiographic (ECG) recordings acquired by a clinical Holter ECG recorder (Global Instrumentation's M12R Holter), which is a wearable device; and iii) heart-rate measurements acquired from a commercial smartwatch (Moto 360 smartwatch by Motorola), which is also a wearable device. ECG recordings were processed to extract the R-peaks position and obtain a reference indirect measurement of the heart rate. A direct measurement of the heart rate was provided by the commercial smartwatch. The dataset here presented could be useful to develop new algorithms for heart-rate detection from contactless devices and to validate contactless heart-rate estimation in comparison to reference heart rate from clinical wearable devices and to heart rate from commercial wearable devices.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/269568 Collegamento a IRIS

2019
Model-based assessment of sex differences in glucose effectiveness and its components
IFMBE Proceedings
Autore/i: Morettini, M.; Ilari, L.; Gobl, C.; Kautzky-Willer, A.; Tura, A.; Pacini, G.; Burattini, L.
Editore: Springer
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Sex differences may assume a key role in condition of impaired glucose metabolism and progression to type 2 diabetes, affecting insulin-dependent processes. However, the presence of sex differences in non-insulin-dependent processes (i.e. glucose effectiveness) has been scarcely investigated. The aim of this study was to detect the presence of sex differences in glucose effectiveness (SG), as assessed by minimal model analysis, in subjects with different degrees of glucose metabolism impairment. Two groups of subjects ranging from normal (NGR, n = 57, males/females: 31/26) to abnormal glucose regulation (AGR, n = 115, males/females 42/73) underwent a 3-h frequently sampled intravenous glucose tolerance test. Minimal model analysis provided SG and its components at zero (GEZI) and at basal (BIE) insulin. Values for SG were 2.52 ± 0.98 10−2 min−1 and 2.81 ± 1.07 10−2 min−1 for males and females in the NGR group, and 2.08 ± 1.21 10−2 min−1 and 2.09 ± 0.98 10−2 min−1 for males and females in the AGR group. No statistically significant difference was found between males and females in both NGR (p = 0.29) and AGR (p = 0.94) groups. Sex differences were not detected for GEZI, which provided the major contribution to SGeither in NGR or AGR group. In conclusion, glucose effectiveness and its components seem to be not affected by sex differences in all glucose tolerance conditions.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/272505 Collegamento a IRIS

2018
Personalizing physical exercise in a computational model of fuel homeostasis
PLOS COMPUTATIONAL BIOLOGY
Autore/i: Palumbo, M. C.; Morettini, M.; Tieri, P.; Diele, F.; Sacchetti, M.; Castiglione, F.
Classificazione: 1 Contributo su Rivista
Abstract: The beneficial effects of physical activity for the prevention and management of several chronic diseases are widely recognized. Mathematical modeling of the effects of physical exercise in body metabolism and in particular its influence on the control of glucose homeostasis is of primary importance in the development of eHealth monitoring devices for a personalized medicine. Nonetheless, to date only a few mathematical models have been aiming at this specific purpose. We have developed a whole-body computational model of the effects on metabolic homeostasis of a bout of physical exercise. Built upon an existing model, it allows to detail better both subjects’ characteristics and physical exercise, thus determining to a greater extent the dynamics of the hormones and the metabolites considered.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/277113 Collegamento a IRIS

2018
PCG-Delineator: an Efficient Algorithm for Automatic Heart Sounds Detection in Fetal Phonocardiography
Computing in Cardiology
Autore/i: Strazza, Annachiara; Sbrollini, Agnese; di Battista, Valeria; Ricci, Rita; Trillini, Letizia; Marcantoni, Ilaria; Morettini, Micaela; Fioretti, Sandro; Burattini, Laura
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Fetal phonocardiography (FPCG) is a non-invasive electronic recording of the acoustic cardiac signals. Unfortunately, FPCG is hidden by high-amplitude noise which makes detection of FPCG waveforms challenging. Aim of the study is to propose PCG-Delineator as an algorithm for automatic detection of the first and second heart sound (S1 and S2, respectively) from FPCG. To this aim, 37 simulated FPCG tracings (Physionet) are filtered by a wavelet-based procedure (4th order Coiflets mother wavelet with 7 decomposition levels) to erase noise. Successively, S1 and S2 are detected. S1 detection procedure is threshold-based (threshold=30% of the filtered FPCG signal maximum amplitude), under the condition that 40ms separate two consecutive S1 sounds. S2 detection procedure is also threshold-based, but under the conditions that S2 has to fall 100ms after preceding S1 and 200ms before successive S1, and that S2 has to have an amplitude lower than 80% that of preceding S1. Sensitivity (SE) and positive predictive values (PPV) were computed. Results indicate that PCG-Delineator was able to reduce noise (our SNR: from -1.1÷7.4dB to 12.9÷17.9dB; P<10-14) and to accurately detect both S1 (SE: 88%; PPV: 91%) and S2 (SE: 77%; PPV:99%). In conclusion, PCG-Delineator is an efficient algorithm for automatic heart sounds detection in FPCG.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/264730 Collegamento a IRIS

2018
GPU-Based Segmented-Beat Modulation Method for Denoising Athlete Electrocardiograms During Training
Computing in Cardiology
Autore/i: Nasim, Amnah; DELLA SANTA, Edoardo; Tanchi, Damiano; Sbrollini, Agnese; Marcantoni, Ilaria; Morettini, Micaela; Burattini, Laura
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Sport-related sudden cardiac death (SRSCD), defined as “death occurring during sport or within one hour of cessation of training”, is the leading cause of death in athletes. SRSCD occurs in the presence of underlying cardiovascular diseases, some of which may be identified by processing electrocardiographic recordings acquired during training (TECGs). A fast and accurate processing of TECGs during or immediately after training is challenging since TECGs are typically highly corrupted by noise and interferences, which may jeopardize their interpretation and identification of abnormal morphologies. The present study evaluated the ability of GPU-based Segmented-Beat Modulation Method (GPUSBMM) to provide a noise-free estimation of TECGs, and to improve the algorithm by GPU acceleration to make it compatible with modern hardware. In this research, 19 6- to-10 min TECGs (sampling frequency: 256 Hz), acquired from 8 subjects while performing 4 different exercise tasks (walk, run, low-resistance bike and high-resistance bike), were analyzed. Results indicate that GPU-SBMM application yielded a significant increase of SNR(dB) (from 1±5 dB to 19±5 dB; p<10-12 ), also when stratifying by exercise tasks. Additionally, a considerable average speedup of 7.67x is achieved using NVIDIA GeForce 740M GPU processor.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/264729 Collegamento a IRIS

2018
T-Wave Alternans in Partial Epileptic Patients
Computing in Cardiology
Autore/i: Marcantoni, Ilaria; Cerquetti, Valeria; Cotechini, Valentina; Lattanzi, Maeva; Sbrollini, Agnese; Morettini, Micaela; Burattini, Laura
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Epilepsy is a chronic neurological disorder, hallmark of which is unpredictable epileptic seizures (ES). The leading cause of death in people with uncontrolled ES is the sudden unexpected death in epilepsy (SUDEP), which is believed to share genes with sudden cardiac death (SCD). Being T-wave alternans (TWA) an ECG index of SCD, aim of this work was to evaluate TWA occurrence in proximity of ES. Electrocardiograms (ECG) from five partial epileptic patients constituting the “Post-Ictal Heart Rate Oscillations in Partial Epilepsy” Database by Physionet were analysed for automatic TWA identification by the heart-rate adaptive match filter (HRAMF). ES onsets and offsets were annotated. ECG segments starting 10min before ES and ending 10min after ES were extracted and further processed to characterize trends of median heart rate, median TWA (mTWA) and maximum TWA (MTWA) in ES proximity. Levels of mTWA were significantly higher than what previously observed in a female healthy population in all ES (46[25;59]µV), pre-ES (31[25;62]µV) and post-ES (30[26;63]µV) conditions. Both mTWA and MTWA tended to increase during ES. Thus, in proximity of ES, our epileptic patients are at increased risk of SCD, possibly associated with SUDEP. Other studies defining TWA role as a biomarker for SUDEP are needed.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/264731 Collegamento a IRIS

2018
Assessment of glucose effectiveness from short IVGTT in individuals with different degrees of glucose tolerance
ACTA DIABETOLOGICA
Autore/i: Morettini, Micaela;   ·, Francesco  Di  Nardo; Burattini, Laura; Fioretti, Sandro; Christian  Göbl,   ·; Alexandra  Kautzky‑Willer,   ·; Giovanni  Pacini,   ·; Andrea  Tura,   ·
Classificazione: 1 Contributo su Rivista
Abstract: Aims Minimal model analysis of intravenous glucose tolerance test (IVGTT) data represents the reference method to assess insulin sensitivity (SI) and glucose effectiveness (SG) that quantify the insulin-dependent and insulin-independent processes of glucose disappearance, respectively. However, test duration (3 h) and need for modeling expertise limit the applicability of this method. Aim of this study was providing a simple predictor of SG applicable to short test (1 h), as previously done with SI. Methods Three groups of subjects reflecting different glucose tolerance degrees underwent a 3 h IVGTT: subjects with normal glucose tolerance (NGT, n = 164), with defective glucose regulation (DGR, n = 191), and with type 2 diabetes (T2D, n = 39). Minimal model analysis provided reference SG and its components at zero (GEZI) and basal (BIE) insulin. The simple predictor CSG (calculated SG) was described by the formula CSG = α0 + α1 × KG/Gpeak, being KG the glucose disappearance rate (between 10 and 50 min) and Gpeak the maximum of the glucose curve during the test; α0 and α1 coefficients were provided by linear regression analysis. Results CSG and SG showed a markedly significant relationship in the whole dataset (r = 0.72, p < 0.0001) and in the single groups (r = 0.70 in NGT, r = 0.71 in DGR and r = 0.70 in T2D, p < 0.0001 for all); α1 × KG/Gpeak was significantly related to GEZI (r ≥ 0.60). Conclusions The interest for insulin-independent glucose disappearance is increasing, due to the recent availability of SGLT2 pharmacological agents, lowering glycemic levels without requiring insulin action. This study proposes a reliable predictor of SG based on IVGTT lasting 1 h only, and not requiring mathematical modeling skills.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/260624 Collegamento a IRIS

2018
Surface electromyography low-frequency content: Assessment in isometric conditions after electrocardiogram cancellation by the Segmented-Beat Modulation Method
INFORMATICS IN MEDICINE UNLOCKED
Autore/i: Sbrollini, Agnese; Strazza, Annachiara; Candelaresi, Silvia; Marcantoni, Ilaria; Morettini, Micaela; Fioretti, Sandro; Di Nardo, Francesco; Burattini, Laura
Classificazione: 1 Contributo su Rivista
Abstract: Background: Surface electromyography (SEMG) is widely used in clinics for assessing muscle functionality. All procedures proposed for noise reduction alter SEMG spectrum, especially in the low-frequency band (below 30 Hz). Indeed, low-frequency band is generally addressed to motion artifacts and electrocardiogram (ECG) interference without any further investigation on the possibility of SEMG having significant spectral content. The aim of the present study was evaluating SEMG frequency content to understand if low-frequency spectral content is negligible or, on the contrary, represents a significant SEMG portion potentially providing relevant clinical information. Method: Isometric recordings of five muscles (sternocleidomastoideus, erectores spinae at L4, rectus abdominis, rectus femoris and tibialis anterior) were acquired in 10 young healthy voluntary subjects. These recordings were not affected by motion artifacts by construction and were pre-processed by the Segmented-Beat Modulation Method for ECG deletion before performing spectral analysis. Results: Results indicated that SEMG frequency content is muscle and subject dependent. Overall, the 50th[25th;75th] percentiles spectrum median frequency and spectral power below 30 Hz were 74[54; 87] Hz and 18[10; 31] % of total (0–450 Hz) spectral power. Conclusions: Low-frequency spectral content represents a significant SEMG portion and should not be neglected.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/262204 Collegamento a IRIS

2018
Electrocardiogram Derived Respiratory Signal through the Segmented-Beat Modulation Method
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Autore/i: Pambianco, Benedetta; Sbrollini, Agnese; Marcantoni, Ilaria; Morettini, Micaela; Fioretti, Sandro; Burattini, Laura
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Respiration rate and variability are indicators of health-condition changes. In chronic disease management, it is becoming increasingly desirable to use wearable devices in order to minimize invasiveness and maximize comfort. However, not all wearable devices integrate sensors for direct acquisition of respiratory (DAR) signal. In these cases, the breathing extraction can be done through indirect methods, typically from the electrocardiogram (ECG). The aim of the present study is to propose a single-ECG-lead procedure based on the Segmented-Beat Modulation Method (SBMM) as a suitable tool for ECG-derived respiratory (EDR) signal estimation and respiration frequency (RF) identification. Clinical data consisted of combined measurements of two-lead (I and II) ECG and DAR signals from 20 healthy subjects ('CEBS' database by Physionet). Each respiration-affected ECG lead was submitted to a specifically designed SBMMbased procedure for EDR estimation by ECG subtraction. RF from EDR and DAR were identified as the frequency at which the Fourier spectrum has a maximum in the 0.07-1.00 Hz frequency range. Results indicated that mean RF values over the population from EDR signals (0.27 ± 0.09 Hz and 0.27 ± 0.09 Hz from leads I and II, respectively) were not significantly different from that from DAR (0.28 ± 0.09 Hz). Moreover, differences in RF identification (0.01 ± 0.03 Hz and 0.00 ± 0.02 Hz from leads I and II, respectively) were, on average not significantly different from 0. Thus, SBMM-based procedure is robust and accurate for EDR estimation and RF identification.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/262588 Collegamento a IRIS

2018
Automatic T-Wave Alternans Identification in Indirect and Direct Fetal Electrocardiography
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Autore/i: Marcantoni, Ilaria; Sbrollini, Agnese; Burattini, Luca; Morettini, Micaela; Fioretti, Sandro; Burattini, Laura
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Fetal T-wave alternans (TWA) is a still littleknown marker for severe fetus-heart instabilities and may be related to some currently unjustified fetal deaths. Automatically detecting TWA on direct fetal electrocardiograms (DFECG) means possibility of providing fetuses the right treatment during delivery. Instead, automatically identifying TWA on indirect fetal electrocardiograms (IFECG) means possibility of providing fetuses the right treatment even during pregnancy, when taking actions for outcome improvement is still possible. Moreover, TWA identification from IFECG is noninvasive, and thus safe for both fetuses and mothers. The aim of this work was testing the heart-rate adaptive match filter (HRAMF) for automatic TWA identification in IFECG and comparing HRAMF performance in IFECG against DFECG. To this aim, simultaneously recorded DFECG and IFECG tracings from 5 healthy fetuses were used ('Abdominal and Direct Fetal Electrocardiogram Database' from Physionet). TWA measurements (frequency, mean amplitude, maximum amplitude, and amplitude standard deviation) in IFECG (1.09±0.04 Hz, 11±5 μV, 21±12 μV and 7±3 μV) were of the same order of magnitude of those in DFECG (1.07±0.02 Hz, 9±2 μV, 30±11 μV and 6±2 μV). Moreover, a direct correlation (ñ) was found between maximum TWA and fetal heart rate (IFECG: ρ=0.999; P=0.022; DEFEG: ρ=0.642; P=0.243). Thus, HRAMF was able to detect TWA from IFECG as well as from DFECG.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/262587 Collegamento a IRIS

2018
Automatic Identification and Classification of Fetal Heart-Rate Decelerations from Cardiotocographic Recordings
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Autore/i: Sbrollini, Agnese; Carnicelli, Amalia; Massacci, Alessandra; Tomaiuolo, Leonardo; Zara, Tommaso; Marcantoni, Ilaria; Burattini, Luca; Morettini, Micaela; Fioretti, Sandro; Burattini, Laura
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Cardiotocography (CTG) consists in the simultaneous recording of two distinct traces, the fetal heart rate (FHR; bpm) and the maternal uterine contractions (UCs; mmHg). CTG analysis consists in the evaluation of specific features of traces, among which fetal decelerations (DECs) are considered the 'center-stage' since possibly related to fetal distress. DECs are classified based on their duration and occurrence in relation to UCs as prolonged, early, late and variable; each class associates to a specific status of the fetus health. Typically, CTG traces are visually interpreted; however, computerized CTG analysis may overcome subjectivity in CTG interpretation. Thus, this study proposes a new automatic algorithm for computerized identification and classification of DECs. The algorithm was tested on the 552 CTG recordings constituting the 'CTU-CHB intra-partum CTG database' of Physionet. Of these, 470 (85.15%) were found suitable for automatic DECs identification and classification. Overall, 5888 DECs were identified, of which 3255 (55.28%) were classified while the other 2633 (44.72%) remained unclassified due to very strict preliminary classification criteria (now required for avoiding misclassifications). Among the classified DECs, 468 (14.38%) were classified as prolonged, 1498 (46.02%) as early, 32 (0.98%) as late, 1257 (38.62%) as variable. Thus, among the classified DECs, the most common are the early and the variable ones (overall 84.64%), the occurrence of which ranged from 0 to 14 DECs per recording. These findings are in agreement with what reported in literature. In conclusion, the proposed algorithm for automatic DECs identification and classification represents a useful tool for computerized CTG analysis.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/262590 Collegamento a IRIS

2018
TWA Simulator: a Graphical User Interface for T-wave Alternans
Computing in Cardiology
Autore/i: Morettini, Micaela; Marchesini, Lorenzo; Pettinari, LUCA ALBERTO; Tigrini, Andrea; Marcantoni, Ilaria; Sbrollini, Agnese; Burattini, Laura
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: T-wave alternans (TWA) is an every-other-beat fluctuation of the T-wave amplitude, often at microvolt (invisible) levels. It is recognized as an important risk index of severe ventricular arrhythmias, leading sometimes to sudden cardiac arrest. Many algorithms for automatic detection and quantification of TWA have been proposed; when applied to the same electrocardiogram (ECG), they may provide a different TWA quantification, making interpretation of differences difficult. Aim of this work is to propose TWA Simulator as a useful tool to validate and compare TWA identification methods. TWA Simulator is a user-friendly MATLAB graphical user interface (GUI) able to generate, model, visualize and store simulated ECG (SECG) affected by TWA of known morphology and amplitude. SECG is constructed by a Nfold repetition of a template, constituted by a real and clean ECG beat. Both number of beats and RR inter-beat variability can be set by the user. Both direct and inverted TWA can be simulated. Direct TWA is simulated by adding a waveform (among four possibility) to every other T wave; inverted TWA is simulated by changing T-wave polarity in every-other SECG beat. Availability of TWA Simulator would allow efficient validation and comparison of automatic TWA identification methods by helping interpretation of results
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/264735 Collegamento a IRIS

2018
Automatic Identification of Atrial Fibrillation by Spectral Analysis of Fibrillatory Waves
Computing in Cardiology
Autore/i: Sbrollini, Agnese; Cicchetti, Krizia; DE MARTINIS, Alessia; Marcantoni, Ilaria; Morettini, Micaela; Burattini, Laura
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: A heart affected by atrial fibrillation (AF) presents atrial cells that depolarize in many sites, generating a chaotic electrical activity. On the electrocardiogram (ECG), this activity reflects in the appearance of fibrillatory (F) waves, consisting of low-amplitude oscillations at 4-10 Hz. Aim of the present study is to propose an automatic AF identification method based on F-wave frequency analysis in 10 s ECGs. To this aim, 10 s ECG from 90 healthy subjects (HSs) and 50 AF patients (AFPs) were considered. ECGs were processed by the segmented beat modulation method to reduce components in the F-wave band. Then, the power spectral density (PSD) was computed and the F-wave frequency ratio (FWFR), defined as the ratio between the spectral area in the F-wave frequency band and the total spectral area, was computed. FWFR ability to discriminate AFPs from HSs was evaluated by analyzing the area under the curve (AUC) of the receiver operating characteristic, and by computation of sensitivity, specificity and accuracy. FWFR values were higher in AFPs than in HSs (P<10-11). AUC was at least 85%, whereas sensitivity, specificity and accuracy were at least 84%, 69% and 81%, respectively. In conclusion, F-wave frequency evaluation by FWFR represents a promising clinical tool to automatically identify AF.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/264734 Collegamento a IRIS

2018
eCTG: an automatic procedure to extract digital cardiotocographic signals from digital images
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
Autore/i: Sbrollini, Agnese; Agostinelli, Angela; Marcantoni, Ilaria; Morettini, Micaela; Burattini, Luca; Di Nardo, Francesco; Fioretti, Sandro; Burattini, Laura
Classificazione: 1 Contributo su Rivista
Abstract: Background and objective: Cardiotocography (CTG), consisting in the simultaneous recording of fetal heart rate (FHR) and maternal uterine contractions (UC), is a popular clinical test to assess fetal health status. Typically, CTG machines provide paper reports that are visually interpreted by clinicians. Consequently, visual CTG interpretation depends on clinician's experience and has a poor reproducibility. The lack of databases containing digital CTG signals has limited number and importance of retrospective studies finalized to set up procedures for automatic CTG analysis that could contrast visual CTG interpretation subjectivity. In order to help overcoming this problem, this study proposes an electronic procedure, termed eCTG, to extract digital CTG signals from digital CTG images, possibly obtainable by scanning paper CTG reports. Methods: eCTG was specifically designed to extract digital CTG signals from digital CTG images. It includes four main steps: pre-processing, Otsu's global thresholding, signal extraction and signal calibration. Its validation was performed by means of the “CTU-UHB Intrapartum Cardiotocography Database” by Physionet, that contains digital signals of 552 CTG recordings. Using MATLAB, each signal was plotted and saved as a digital image that was then submitted to eCTG. Digital CTG signals extracted by eCTG were eventually compared to corresponding signals directly available in the database. Comparison occurred in terms of signal similarity (evaluated by the correlation coefficient ρ and the mean signal error MSE) and clinical features (including FHR baseline and variability; number, amplitude and duration of tachycardia, bradycardia, acceleration and deceleration episodes; number of early, variable, late and prolonged decelerations; and UC number, amplitude, duration and period). Results: The value of ρ between eCTG and reference signals was 0.85 (P < 10−560) for FHR and 0.97 (P < 10−560) for UC. On average, MSE value was 0.00 for both FHR and UC. No CTG feature was found significantly different when measured in eCTG vs. reference signals. Conclusions: eCTG procedure is a promising useful tool to accurately extract digital FHR and UC signals from digital CTG images.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/255236 Collegamento a IRIS

2017
IVGTT-based simple assessment of glucose tolerance in the Zucker fatty rat: Validation against minimal models
PLOS ONE
Autore/i: Morettini, Micaela; Faelli, Emanuela; Perasso, Luisa; Fioretti, Sandro; Burattini, Laura; Ruggeri, Piero; DI NARDO, Francesco
Classificazione: 1 Contributo su Rivista
Abstract: For the assessment of glucose tolerance from IVGTT data in Zucker rat, minimal model methodology is reliable but time- and money-consuming. This study aimed to validate for the first time in Zucker rat, simple surrogate indexes of insulin sensitivity and secretion against the glucose-minimal-model insulin sensitivity index (SI) and against first- (φ1) and second-phase (φ2) β-cell responsiveness indexes provided by C-peptide minimal model. Validation of the surrogate insulin sensitivity index (ISI) and of two sets of coupled insulinbased indexes for insulin secretion, differing from the cut-off point between phases (FPIR3- SPIR3, t = 3 min and FPIR5- SPIR5, t = 5 min), was carried out in a population of ten Zucker fatty rats (ZFR) and ten Zucker lean rats (ZLR). Considering the whole rat population (ZLR+ZFR), ISI showed a significant strong correlation with SI (Spearman's correlation coefficient, r = 0.88; P<0.001). Both FPIR3 and FPIR5 showed a significant (P<0.001) strong correlation with φ1 (r = 0.76 and r = 0.75, respectively). Both SPIR3 and SPIR5 showed a significant (P<0.001) strong correlation with φ2 (r = 0.85 and r = 0.83, respectively). ISI is able to detect (P<0.001) the well-recognized reduction in insulin sensitivity in ZFRs, compared to ZLRs. The insulin-based indexes of insulin secretion are able to detect in ZFRs (P<0.001) the compensatory increase of first- and second-phase secretion, associated to the insulinresistant state. The ability of the surrogate indexes in describing glucose tolerance in the ZFRs was confirmed by the Disposition Index analysis. The model-based validation performed in the present study supports the utilization of low-cost, insulin-based indexes for the assessment of glucose tolerance in Zucker rat, reliable animal model of human metabolic syndrome.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/245897 Collegamento a IRIS

2017
Statistical baseline assessment in cardiotocography
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Autore/i: Agostinelli, Angela; Braccili, Eleonora; Marchegiani, Enrico; Rosati, Riccardo; Sbrollini, Agnese; Burattini, Luca; Morettini, Micaela; Di Nardo, Francesco; Fioretti, Sandro; Burattini, Laura
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Cardiotocography (CTG) is the most common non-invasive diagnostic technique to evaluate fetal well-being. It consists in the recording of fetal heart rate (FHR; bpm) and maternal uterine contractions. Among the main parameters characterizing FHR, baseline (BL) is fundamental to determine fetal hypoxia and distress. In computerized applications, BL is typically computed as mean FHR±ΔFHR, with ΔFHR=8 bpm or ΔFHR=10 bpm, both values being experimentally fixed. In this context, the present work aims: to propose a statistical procedure for ΔFHR assessment; to quantitatively determine ΔFHR value by applying such procedure to clinical data; and to compare the statistically-determined ΔFHR value against the experimentally-determined ΔFHR values. To these aims, the 552 recordings of the 'CTU-UHB intrapartum CTG database' from Physionet were submitted to an automatic procedure, which consisted in a FHR preprocessing phase and a statistical BL assessment. During preprocessing, FHR time series were divided into 20-min sliding windows, in which missing data were removed by linear interpolation. Only windows with a correction rate lower than 10% were further processed for BL assessment, according to which ΔFHR was computed as FHR standard deviation. Total number of accepted windows was 1192 (38.5%) over 383 recordings (69.4%) with at least an accepted window. Statistically-determined ΔFHR value was 9.7 bpm. Such value was statistically different from 8 bpm (P<10-19) but not from 10 bpm (P=0.16). Thus, ΔFHR=10 bpm is preferable over 8 bpm because both experimentally and statistically validated.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/255427 Collegamento a IRIS

2017
CTG Analyzer: A graphical user interface for cardiotocography
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Autore/i: Sbrollini, Agnese; Agostinelli, Angela; Burattini, Luca; Morettini, Micaela; Di Nardo, Francesco; Fioretti, Sandro; Burattini, Laura
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Cardiotocography (CTG) is the most commonly used test for establishing the good health of the fetus during pregnancy and labor. CTG consists in the recording of fetal heart rate (FHR; bpm) and maternal uterine contractions (UC; mmHg). FHR is characterized by baseline, baseline variability, tachycardia, bradycardia, acceleration and decelerations. Instead, UC signal is characterized by presence of contractions and contractions period. Such parameters are usually evaluated by visual inspection. However, visual analysis of CTG recordings has a well-demonstrated poor reproducibility, due to the complexity of physiological phenomena affecting fetal heart rhythm and being related to clinician's experience. Computerized tools in support of clinicians represents a possible solution for improving correctness in CTG interpretation. This paper proposes CTG Analyzer as a graphical tool for automatic and objective analysis of CTG tracings. CTG Analyzer was developed under MATLAB®; it is a very intuitive and user friendly graphical user interface. FHR time series and UC signal are represented one under the other, on a grid with reference lines, as usually done for CTG reports printed on paper. Colors help identification of FHR and UC features. Automatic analysis is based on some unchangeable features definitions provided by the FIGO guidelines, and other arbitrary settings whose default values can be changed by the user. Eventually, CTG Analyzer provides a report file listing all the quantitative results of the analysis. Thus, CTG Analyzer represents a potentially useful graphical tool for automatic and objective analysis of CTG tracings.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/255424 Collegamento a IRIS

2017
Overnight T-wave alternans in sleep apnea patients
Computing in Cardiology
Autore/i: Burattini, Laura; Ciotti, Ilaria; D'Ignazio, Michela; Miccoli, Alessandro; Agostinelli, Angela; Sbrollini, Agnese; Morettini, Micaela; Di Nardo, Francesco; Fioretti, Sandro
Editore: IEEE Computer Society
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Sleep apnea (SA) is linked to cardiovascular complications and to an increased risk of sudden cardiac death. Microvolt T-wave alternans (TWA) is a noninvasive electrocardiographic (ECG) index of cardiovascular risk; its rate of occurrence in SA patients remains unknown. Thus, this study investigated the occurrence of TWA in SA patients during night. To this aim, overnight ECG recordings of 16 SA patients were analyzed for TWA identification by means of our heart rate adaptive match filter. Results indicate that overnight TWA was characterized by a low mean amplitude (mean TWA: 6±3 µV). However, higher-amplitude transient TWA episodes (max TWA: 29±21 µV) occurred overnight, sometimes when patients were awake (max TWA: 33±18 µV; 56% of cases) and sometimes when patients were sleeping (max TWA: 24±23 µV; 44% of cases with 13%, 19%, 6% and 6% during sleep stage 1, 2, 3 and 4, respectively). In only 3 subjects (19%) TWA peaks occurred during an SA episode: during obstructive apnea with arousal in two cases (max TWA of 7 µV and 17 µV, during stages 1 and 2, respectively) and during hypoapnea with arousal in one case (max TWA of 6 µV while awake). Thus, SA patients show significant transient overnight TWA episodes, not necessarily occurring during a SA episode.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/259391 Collegamento a IRIS

2017
Fetal phonocardiogram denoising by wavelet transformation: Robustness to noise
Computing in Cardiology
Autore/i: Sbrollini, Agnese; Strazza, Annachiara; Caragiuli, Manila; Mozzoni, Claudia; Tomassini, Selene; Agostinelli, Angela; Morettini, Micaela; Fioretti, Sandro; Di Nardo, Francesco; Burattini, Laura
Editore: IEEE Computer Society
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Fetal phonocardiography (fPCG) is a clinical test to assess fetal wellbeing during pregnancy, labor and delivery. Still, its interpretation may be jeopardized by the presence of noise. Specifically, fPCG is typically corrupted by maternal heart and body organs sounds, fetal movements noise and surrounding environment noise. Thus, appropriate filtering procedures have to be applied in order to make fPCG clinically usable. Wavelet transformation (WT) has been proposed to filter fPCG; however, WT robustness to noise remains unknown. Thus, aim of the present work is to evaluate WT ability and robustness to denoise fPCG characterized by varying signal-to-noise ratios (SNR). To this aim a filtering procedure based on Coiflets mother wavelet (4th order, 7 levels of decomposition) was applied to 37 fPCG simulated tracings, all available in the Simulated Fetal PCGs database by Physionet. Original SNR values ranged from -1.38 dB to 4.54 dB; after application of WT-filtering procedure to fPCG, SNR increased significantly, ranging from 12.95 dB to 17.94 dB (P<10- 14). Moreover, SNR values before and after filtering were associated by a low correlation (ρ=0.4; P=0.01). Eventually, WT filtering introduced no fPCG signal delay and left heart rate unaltered. Thus, WT filtering is a suitable and robust technique to denoise fPCG signals.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/259394 Collegamento a IRIS

2017
T-Wave alternans identification in direct fetal electrocardiography
Computing in Cardiology
Autore/i: Marcantoni, Ilaria; Vagni, Marica; Agostinelli, Angela; Sbrollini, Agnese; Morettini, Micaela; Burattini, Luca; Di Nardo, Francesco; Fioretti, Sandro; Burattini, Laura
Editore: IEEE Computer Society
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Very little is known about the incidence and etiology of fetal T-wave alternans (TWA), an electrophysiologic phenomenon potentially associated to fetal suboptimal outcomes. Thus, availability of automatic methods for quantification of TWA from digital electrocardiograms (ECG) is desirable, since TWA occurrence might indicate the need of taking actions before or during delivery. The heart-rate adaptive match filter (HRAMF) is a wellestablished method to identify TWA in adult ECG. Aim of the present study was to investigate the possibility of using HRAMF to identify and quantify TWA also in direct fetal ECG (DFECG) recordings. To this aim, HRAMF was applied to 5 min-long DFECG acquired during delivery (“Abdominal and Direct Fetal Electrocardiogram Database” by Physionet) of five healthy fetuses. Significant levels of TWA were measured in all DFECG. Specifically, on average, TWA was quite high in amplitude (9±2 µV) and variable in time, as indicated by values of standard deviation (6±2 µV) and maximum (28±10 µV) of TWA amplitude. Eventually, a positive correlation (ρ=0.68) was observed between maximum TWA and fetal heart rate, even though the limited number of recordings makes this result preliminary. In conclusion, HRAMF proved to be a suitable tool to automatically identify TWA from DFECG.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/259390 Collegamento a IRIS

2017
AThrIA: A new adaptive threshold identification algorithm for electrocardiographic P Waves
Computing in Cardiology
Autore/i: Sbrollini, Agnese; Mercanti, Sofia; Agostinelli, Angela; Morettini, Micaela; Di Nardo, Francesco; Fioretti, Sandro; Burattini, Laura
Editore: IEEE Computer Society
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Proposed algorithms for P-wave identification and segmentation usually search for it within a window just before the R peak, thus hypothesizing the presence of at most one P wave, as it is in a normal electrocardiographic (ECG) tracings. In presence of abnormal atrial depolarization, however, there might be no P waves (as in atrial fibrillation) or multiple P waves (as in second- or third-degree atrioventricular blocks). Thus, this study proposes a new Adaptive Threshold Identification Algorithm (AThrIA) for ECG P-waves whose most innovative feature is to look for P waves all along the heartbeat, potentially allowing multiple Pwaves identification. AThrIA ability to identify and segment (finding onset, maximum and offset) P waves was tested in simulated and experimental ECG tracings with no P waves, one P wave and two P waves, respectively. All P waves involved in the study were annotated. Results indicate that AThrIA correctly identified all P waves (no false-negative or false-positive detections). Segmentation errors were 0 ms for the simulated ECG tracings, and no more than 10 ms for the experimental tracings. Thus, AThrIA represents a promising tool for P-wave identification and segmentation in both physiological (one P wave) and pathological (none or multiple P waves) conditions.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/259393 Collegamento a IRIS

2017
Second heart sound onset to identify T-wave offset
Computing in Cardiology
Autore/i: Sbrollini, Agnese; Bartoli, Marta Beghella; Agostinelli, Angela; Morettini, Micaela; Di Nardo, Francesco; Fioretti, Sandro; Burattini, Laura
Editore: IEEE Computer Society
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Phonocardiography (PCG) second heart sound represents aortic-pulmonary valves closure and beginning of isovolumetric relaxation of the ventricles. Electrocardiography (ECG) T wave represents electrical repolarization of the ventricles. Ventricular electrical repolarization is known to drive ventricular mechanical relaxation. Thus, the aim of the present study was to investigate whether, in normal conditions, second heart sound onset (S2on) matches in time T-wave offset (Toff) so that S2on may be used to identify Toff. To this aim, 99 couples of simultaneously recorded short (around 30 s PCG and ECG) signals relative to normal subjects (selected from PhysioNet/CinC Challenge 2016: Training Set A) were analyzed. S2on was identified by application of our newly developed threshold-based algorithm to the median beat of the PCG envelope. Instead, Toff was identified by application of the Laguna and Thakor algorithm to the median ECG beat. Median time-distance (δt) between S2on and Toff was 5 ms (P=0.007). Thus, in normal conditions, S2on and Toff differ on average of 5 ms, whose meaning remain to be defined. Still, 5 ms is included in the Toff identification variability (of the order of tens ms) due to different Toff identification methods and electrocardiographic leads. Consequently, in normal condition, S2on may be used to estimate Toff
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/259389 Collegamento a IRIS

2017
No changes in glucose effectiveness in condition of reduced insulin action but preserved glucose tolerance as assessed by minimal model analysis
IFMBE Proceedings
Autore/i: Morettini, Micaela; DI NARDO, Francesco; Fioretti, Sandro; Pacini, G.; Tura, A.; Burattini, Laura
Editore: Springer Verlag
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Glucose effectiveness (SG) represents the ability of glucose per se, under basal insulin concentrations, to stimulate its own uptake and to suppress its own production. SG and its two components BIE (Basal Insulin Effect) and GEZI (Glucose Effectiveness at Zero Insulin) are known to decline in subjects whose glycemic status worsens, but no study aimed to analyze whether changes may occur even before, when a normal glucose tolerance status is still preserved but insulin resistance has already arisen. To investigate this issue, SG, BIE and GEZI were estimated from the minimal model interpretation of frequently sampled intravenous glucose tolerance (FSIGT) test data in two groups of subjects with normal glucose tolerance (basal glycemia < 5.6 mmol/l): a group of control participants (CNT, n=50) and a group of subjects with pathologies or conditions causing insulin resistance (IR, n=50). No difference in mean values of SG was observed in the IR with respect to the CNT group (2.3 ± 0.9 vs. 2.5 ± 0.9 10-2 min-1; p = 0.17). BIE was found to be the minor component of SG in both CNT and IR group. The GEZI component provided a significantly higher proportional contribution to SG in the IR with respect to CNT (89% vs. 81% of SG, p <0.0001). In proportion, a significantly lower contribution was provided by BIE in IR group (11 ± 1 vs. 18 ± 1, p <0.0001). These results indicate that, at the real starting phase of the process of glucose tolerance impairment (reduced insulin action but normal tolerance), no variation in SG occurs with respect to normality. An increased proportional contribution of GEZI, when BIE declines, may allow the maintenance of normal glucose effectiveness.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/250219 Collegamento a IRIS

2017
Association between accelerations and decelerations of fetal heart rate
IFMBE Proceedings
Autore/i: Agostinelli, Angela; Belgiovine, G.; Fiorentino, M. C.; Turri, G.; Sbrollini, Agnese; Burattini, Laura; Morettini, Micaela; DI NARDO, Francesco; Fioretti, Sandro; Burattini, Laura
Editore: Springer Verlag
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Cardiotocography (CTG) is the most popular test for establishing the fetal health status. Among its characterizing features there are the fetal heart rate (FHR) accelerations (ACC), usually considered a sign of fetal well-being; and decelerations (DEC), some of which may indicate the risk of fetal hypoxia. Thus, ACC and DEC are usually considered independent phenomena possibly providing opposite information on the fetus clinical status. CTG is typically analyzed by visual inspection; still a computerized analysis may provide a more objective CTG interpretation and precise ACC and DEC characterization. Aim of the present study is to propose an automatic procedure for ACC and DEC identification and characterization, and to investigate a potential relationship between their occurrence. The 552 tracings of the Physionet “CTU-CHB intra-partum CTG database” were analyzed according to a procedure that includes: FHR pre-processing; 20 min windowing; baseline estimation; and ACC and DEC identification and characterization. Specifically, ACC and DEC were defined as FHR deviations from baseline of at least 15 bpm for at least 15 s and then characterized in terms of length (s), amplitude (bpm) and area (length·amplitude; bpm·s). Only 383 (69.4%) CTG recordings showed sufficiently good FHR signal quality to be enrolled in the study. Number of DEC per window was significantly higher than ACC (4.0 vs 2.5; P<10-14). DEC were characterized by a comparable length but higher amplitude and area than ACC (LNG: 56 s vs 61 s, P=0.2573; AMP: 12 bpm vs 10 bpm, P<10-11; AREA: 688 s·bpm vs 618 s·bpm, P=0.0032). DEC total area in a 20-min window was higher than that of ACC (3074 s·bpm vs 2007 s·bpm, P<10-9), but such areas were also strictly correlated (ρ=0.72; P<10-62). Thus, in a CTG recording, ACC and DEC are not independent phenomena but their occurrence is strictly associated.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/250213 Collegamento a IRIS

2017
Simple assessment of insulin sensitivity in the zucker rat
IFMBE Proceedings
Autore/i: Morettini, Micaela; Faelli, E.; Perasso, L.; Fioretti, Sandro; Burattini, Laura; Ruggeri, P.; DI NARDO, Francesco
Editore: Springer Verlag
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The model-based assessment of insulin sensitivity in Zucker rat from Intravenous Glucose Tolerance Test (IVGTT) data is a common procedure. The minimal model methodology provides a very reliable assessment but requires specific competence for running the model. The aim of this study was presenting calculated SI (CSI), as a surrogate index for the simple assessment of insulin sensitivity in the Zucker Rat from IVGTT data. To this aim 25 Zucker Lean Rats (ZLR) and 25 Zucker Fatty Rats (ZFR) were considered. Reference insulin sensitivity (SI) was estimated in each rat through the minimal model methodology. CSI is defined as the ratio between the rate of glucose disappearance (KG) and the mean supra-basal area under the insulin curve during the test (ΔAUCINS), corrected by the proportionality term, α. Regression analysis between SI and KG/ΔAUCINS was performed to identify the α coefficient. Results showed as the computed value of CSI presented a high correlation (r = 0.89, R-square = 0.80 and p < 0.0001, slope ≈1) with SI. Mean value of CSI over the whole population was not significantly different from correspondent SI value (p = 0.17). CSI is able to detect the well-known reduction of insulin sensitivity in the ZFR group (1.0±0.1 vs. 5.0±0.7 min-1/μU·ml-1, p < 0.001), in accordance with the results provided by SI. In conclusion, the present study proposes CSI, as a suitable empiric index for a simple and reliable assessment of insulin sensitivity in Zucker rat and able to provide the same quantitative information of model-based SI.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/250217 Collegamento a IRIS

2017
CaRiSMA 1.0: Cardiac risk self-monitoring assessment
THE OPEN SPORTS SCIENCES JOURNAL
Autore/i: Agostinelli, Angela; Morettini, Micaela; Sbrollini, Agnese; Maranesi, Elvira; Migliorelli, Lucia; Di Nardo, Francesco; Fioretti, Sandro; Burattini, Laura
Classificazione: 1 Contributo su Rivista
Abstract: Background: Sport-related sudden cardiac death (SRSCD) can only be fought through prevention. Objective: The aim of this study is to propose an innovative software application, CaRiSMA 1.0 (Cardiac Risk Self-Monitoring Assessment), as a potential tool to help contrasting SRSCD and educating to a correct training. Methods: CaRiSMA 1.0 analyzes the electrocardiographic and heart-rate (HR) signals acquired during a training session through wearable sensors and provides intuitive graphical outputs consisting of two traffic lights, one related to cardiac health, based on resting QTc (a parameter quantifying the duration of ventricular contraction and subsequent relaxation), and one related to training, based on exercise HR. Safe and worthwhile training sessions have green traffic lights. A red QTc traffic light indicates the need of a medical consultation, whereas a red HR traffic light indicate the need of a reduction of training intensity. By way of example, CaRiSMA 1.0 was applied to sample data acquired in 10 volunteers (age= 27±11 years; males/females 3/7). Results: Two acquisitions (20.0%) were rejected because too noisy, indicating that wearable sensors may record poor quality signals. The QTc traffic light was red in 1 case, indicating that people practicing sport may not be aware of being at risk. The HR traffic light was red in 0 cases. Conclusion: CaRiSMA 1.0 is a software application that, for the first time in the sport context, uses QTc, the most important index of cardiac risk in clinics. Thus, it has the potential for giving a contribution in the fight against SRSCD.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/252423 Collegamento a IRIS

2017
Epidemiology/Genetics
DIABETES
Autore/i: Morettini, Micaela; DI NARDO, Francesco; Burattini, Laura; Fioretti, Sandro; Tura, Andrea; Pacini, Giovanni
Classificazione: 1 Contributo su Rivista
Abstract: Two are the main processes regulating post-challenge glucose uptake: one insulin-dependent, and the other mainly due to glucose disappearance per se (glucose effectiveness, SG, min-1), accounting for 60-80% of the whole disappearance. Aim of this study was providing an easy method for assessing SG with a short IVGTT (regular). Three groups of subjects were considered: CNT (control subjects, with normal glucose tolerance: n=158), PRE (subjects with prediabetes and/or pathologies causing insulin resistance: n=220), and T2D (subjects with type 2 diabetes: n=31). Fasting glucose and insulin (mean±SD) were 4.7±0.6, 4.8±0.9, 5.9±1.0 mmol·L-1 and 8.3±3.8, 12.3±9.3, 11.0±4.3 pmol·L-1, for CNT, PRE, T2D, respectively. Reference SG was assessed by Minimal Model analysis. In all grouped subjects, regression analyses were performed to identify a simple predictor (calculated SG, CSG) of reference SG, yielding CSG=α0+α1·KG/Gpeak, with KG slope of the glucose curve (10-50 min), Gpeak maximum glucose, α0=0.007 and α1=0.141. We found SG=0.022±0.010 min-1 and CSG=0.021±0.007 min-1. CSG showed excellent correlation with SG (r=0.65, p<0.001). Similar results were found in each group (r=0.64, p<0.001 in CNT, r=0.63, p<0.001 in PRE, r=0.75, p<0.001 in T2D). Also, SG and CSG were not significantly different, both in all subjects (p=0.34, paired t-test) and in the single groups (p>0.10). Bland-Altman analysis confirmed the substantial equivalence of the two indices, showing only 5% of samples outside the limits of agreement (both in all subjects and the single groups). When comparing SG and CSG among groups, both indices consistently showed lower values in PRE and T2D compared to CNT (p<0.008 for SG and p<0.0001 for CSG, by ANOVA). In conclusion, the first 50 minutes of the IVGTT are sufficient to yield a reliable estimation of glucose effectiveness through a simple approach, not requiring sophisticated mathematical modeling.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/255420 Collegamento a IRIS

2017
Quantification of fetal ST-segment deviations
Computing in Cardiology
Autore/i: Agostinelli, Angela; Di Cosmo, Mariachiara; Sbrollini, Agnese; Burettini, Luca; Morettini, Micaela; Di Nardo, Francesco; Fioretti, Sandro; Burattini, Laura
Editore: IEEE Computer Society
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: By fetal electrocardiogram (FECG) analysis it has been found that changes in the ST segment are associated with acid-base status, and thus fetus health state. Currently, the most popular estimation of fetal STsegment deviations is performed as ratio between T-wave height and QRS-complex amplitude using the STAN monitor. Thus, this evaluation is indirect because not directly derived from measurements on the ST segment. This study proposes a new procedure for an automated direct quantification of fetal ST-segment deviations, which are described in terms of ST-amplitude and STtrend. Particularly, ST-amplitude corresponds to the maximum of the mean amplitude values obtained through a moving-average (15 ms) operation over the ST segment. Instead, ST-trend corresponds to the difference between the ST-segment amplitudes calculated in the first and the last of three intervals in which the ST segment is divided; thus, ST-trend sign indicates a ST-segment elevation (positive sign) or depression (negative sign). The procedure was evaluated on five direct FECG recordings (in https://physionet.org/physiobank/database/adfecgdb/). Mean values (over population) of ST-amplitude and STtrend were 9.6 ± 5.5 μV and 1.4 ± 2.3 μV, respectively. All found values were validated by visual inspection of the magnified FECG plots.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/259395 Collegamento a IRIS

2017
Separation of superimposed electrocardiographic and electromyographic signals
IFMBE Proceedings
Autore/i: Sbrollini, Agnese; Agostinelli, Angela; Morettini, Micaela; Verdini, Federica; DI NARDO, Francesco; Fioretti, Sandro; Burattini, Laura
Editore: Springer Verlag
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Electrocardiography (ECG) and surface electromyography (SEMG) are two non-invasive tests to evaluate cardiac and muscular functionality, respectively. They are both acquired by placing electrodes on the body surface so they become one the interference of the other. Typically, linear filters are used for ECG and SEMG separation: high-pass filters with cutoff at 20 Hz to attenuate ECG interference in SEMG, and low-pass filters with cut-off at 50 Hz to attenuate SEMG interference in ECG. In spite of that, linear filtering is not adequate due to the presence of a 20-50 Hz frequency-band in which the two signal spectra overlap. The aim of the present study was to evaluate the ability of the Segmented-Beat Modulation Method (SBMM) for ECG and SEMG separation and by accurately maintaining signals characteristics. SBMM is a template-based technique for ECG denoising: under the hypothesis of ECG and SEMG linearly superimposed, it first provides an ECG estimation, and then an SEMG estimation by subtraction. In order to test the method under several conditions, SBMM was applied to simulated as well as clinical recordings with superimposed ECG and SEMG. SBMM was able to accurately estimate both ECG and SEMG in all cases. Indeed, ECG and SEMG were estimated by maintain their features such as amplitude (estimation errors <6%), heart rate and heart-rate variability. Moreover, estimated ECG was always characterized by a spectrum mostly (76.4-100.0%) included in the 0-50 Hz frequency-band, whereas estimated SEMG was always characterized by a spectrum mostly (80.9-95.6%) included in the 20-450 Hz frequency-band. Such results confirm the existence of a 20-50 Hz frequency-band in which ECG and SEMG spectral components are overlapped. Thus, SBMM is a robust filtering procedure to separate superimposed ECG and SEMG.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/250221 Collegamento a IRIS

2016
On the Heart-Rate Signal Provided by the Zephyr BioHarness 3.0
Proceeding of the 8th International workshop on Biosignal Interpretation
Autore/i: Nepi, D.; Agostinelli, Angela; Maranesi, Elvira; Sbrollini, Agnese; Morettini, Micaela; DI NARDO, Francesco; Fioretti, Sandro; Burattini, Laura
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The BioHarness 3 system (BH3) by Zephyr is a wearable cardiac sensor specifically designed for training optimization of professional athletes. BH3 records the electrocardiogram (BH3_ECG) and the heart-rate signal (BH3_HRS). Specifically, BH3_HRS is neither the popular tachogram nor the direct not-uniformly sampled heart-rate sequence as function of time. Consequently, the aim of the present study is to gain more insights on BH3_HRS that, if found reliable, would allow a future evaluation of the possibility of a clinical use of the sensor for cardiac risk evaluation. Data were acquired from an amateur athlete (male, 25 years old) during a 5-min rest followed by a 10 min exercise. R-peak detection was performed on BH3_ECG, and the obtained heart-rate signal (HRS) was low-pass filtered using the following six filters: 3-, 4-, and 5-sample averages and 0.30 Hz, 0.35 Hz, and 0.40 Hz 6th order Butterworth low-pass filters. The filtered HRSs were then compared to BH3_HRS in terms of correlation coefficient (ρ), mean square error (MSE), resting heart-rate variability (HRV) and exercise maximum heart rate. Results indicate that the HRS closest to BH3_HRS was obtained with the 3-point average (ρ=0.9688-0.9991, MSE=0.45-0.47 mV2; comparable resting HRV and exercise maximum heart rate).
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/247675 Collegamento a IRIS

2016
Estimation of second-phase insulin secretion in the Zucker fatty rat
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Autore/i: Morettini, Micaela; DI NARDO, Francesco; Cogo, Carla E.; Faelli, Emanuela; Fioretti, Sandro; Burattini, Laura; Ruggeri, Piero
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The purpose of the present study was to test the efficacy of the empiric index SPIR (Second-phase Insulin Release) in the quantification of second-phase insulin secretion in the Zucker Fatty Rat. SPIR index is defined as the area under the curve of insulin between 8 and 90 min after an Intravenous Glucose Tolerance Test (IVGTT). The validation of such index was performed against the second-phase β-cell responsiveness index (Φ2) provided by C-peptide minimal model. To this aim, Φ2 and SPIR were simultaneously computed from IVGTT data, measured in six Zucker fatty rats (ZFR), 7-to-9week-old, and seven age-matched Zucker lean rats (ZLR). SPIR index showed a significant linear correlation with Φ2 (Pearson's correlation coefficient, r = 0.91, R-square = 0.82, P<0.001). Moreover, both Φ2 (P<0.001) and SPIR (P<0.001) showed a significant increase, in the ZFRs, compared to control group (ZLR). These findings suggest that the SPIR index is able to provide similar information of Φ2, in the evaluation of the second-phase insulin secretion and of its alteration in Zucker Fatty Rats. Thus, the study proposes the SPIR, as a suitable index for a simple, reliable and low-cost quantification of the second-phase insulin secretion in ZFR.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/245028 Collegamento a IRIS

2016
Validation of the Heart-Rate Signal Provided by the Zephyr BioHarness 3.0
Computing in Cardiology 2016
Autore/i: Nepi, Daniele; Sbrollini, Agnese; Agostinelli, Angela; Maranesi, Elvira; Morettini, Micaela; Di Nardo, Francesco; Fioretti, Sandro; Pierleoni, Paola; Pernini, Luca; Valenti, Simone; Burattini, Laura
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The Zephyr BioHarness 3.0 (BH3) is a popular wearable system specifically designed for training optimization of professional athletes. BH3 provides the electrocardiogram (ECG BH3) and the heart-rate signal (HRSBH3). Aim of this study is to evaluate the reliability of HRSBH3 to assess its clinical applicability to the general population for cardiac-risk evaluations. Data were acquired from 10 healthy subjects (age: 34±17 years) during a 5-minutes rest. Since the tachogram represents the standard signal for studying the heart rate (HR) and its variability, ECG BH3 was elaborated in order to get the tachogram (HRSTG). HRSBH3 and HRSTG were compared in terms of mean HR (MHR, bpm), HR standard deviation (HRSD, bpm) and HRSD error (bpm). HRSBH3 and HRSTG provided comparable MHR (73.07±15.53 bpm vs 72.86±15.57 bpm, respectively) while HRSD by HRSBH3 was significantly lower than HRSD by HRS TG (4.51 ±2.29 bpm vs 5.63±2.99 bpm, respectively; P=0.0043). HRSD error was significantly greater than zero (0.20-3.00 bpm; P=0.0043); moreover, it was strongly correlated to HRSD by HRS TG (p=0.82, P=0.0036). Thus, HRS BH3 is appropriate only for sport applications based on MHR estimations, but not to clinical evaluations based on HRV measurements.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/246953 Collegamento a IRIS

2016
Health monitoring in sport through wearable sensors: A novel approach based on heart-rate variability
Lecture Notes in Electrical Engineering
Autore/i: Maranesi, Elvira; Morettini, Micaela; Agostinelli, Angela; Giuliani, Corrado; DI NARDO, Francesco; Burattini, Laura
Editore: Springer Verlag
Classificazione: 2 Contributo in Volume
Abstract: Sudden cardiac death (SCD) is one of the leading cause of death during sport activities. Heart rate (HR) and HR variability (HRV) provide a measure of how the organism adapts to physical fatigue, and can be monitored by commercial wearable sensors. Still, HR and HRV, widely used to optimize a training session, were rarely used to evaluate the athlete’s health-status, even though widely known to provide indexes of risk for SCD. This work, developed in collaboration with Bio-Medical Engineering Development Srl, aims to provide a contribution to the problem of preventive identification of athletes at increased risk of SCD, by developing and testing a low-cost, large-scale procedure for HR and HRV monitoring from signals obtained using comfortable wearable sensors. To this aim a new protocol for the acquisition of the tachogram was proposed. It included recordings of the signals during resting, exercise and recovery phases, to allow evaluation of prevention as well as performance indexes. The procedure was tested on 10 sedentary subjects (SS) and 10 amateur athletes (AA). Compared to SS, AA showed a better health-status, quantified in a lower resting HR (63 bpm vs. 73 bpm; P < 0.005) and a higher resting HRV (29 ms vs. 23 ms; P < 0.05), and a better performance level, quantifies in a lower recovery time (130 ms vs. 174 ms; P < 0.05). Thus, the proposed procedure allows evaluation of both the health-status and the performance level of an athlete, and represents a valuable tool to contrast SCD in sport.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/240332 Collegamento a IRIS

2016
Estimation of first-phase insulin secretion in the Zucker Fatty Rat
IFMBE Proceedings
Autore/i: DI NARDO, Francesco; Morettini, Micaela; Cogo, C. E.; Faelli, E.; Fioretti, Sandro; Burattini, Laura; Ruggeri, P.
Editore: Springer Verlag
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The present study was designed to test the efficacy of the popular index AIRG(i.e. acute insulin response after glucose bolus) in the characterization of the first-phase insulin secretion in the Zucker Fatty Rat. The reliability of the AIRGwas evaluated by direct comparison with the first-phase β-cell responsiveness index (Φ1)provided by C-peptide minimal model. To this aim, AIRG and Φ1were simultaneously computed from IVGTT data, measured in six Zucker fatty rats (ZFR), 7-to-9week-old, and seven age-matched Zucker lean rats (ZLR). In the whole 13 rats population, the AIRG showed a significant linear correlation with Φ1(r = 0.89, P < 0.0001). Moreover, both Φ1(P < 0.05) and AIRG (p<0.001) showed a significant increase, in the ZFRs, compared to control group (ZLR). These findings suggest that the AIRG index is able to provide similar information of Φ1, in the evaluation of the alteration of the first-phase insulin secretion in Zucker Fatty Rats. Thus, the present study proposes the AIRG, as a suitable empiric index for a simple, reliable and low-cost quantification of the first-phase insulin secretion in Zucker Fatty Rats. © Springer International Publishing Switzerland 2016.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/236266 Collegamento a IRIS

2016
The relative role of insulin action and secretion in experimental animal models of metabolic syndrome
IFMBE Proceedings
Autore/i: Morettini, Micaela; DI NARDO, Francesco; Cogo, C. E.; Faelli, E.; Fioretti, Sandro; Burattini, Laura; Ruggeri, P.
Editore: Springer Verlag
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: In the present study we evaluated insulin action and secretion in a group of 7 young Zucker fatty rats (ZFR), and in a group of 8 spontaneously hypertensive rats (SHR), compared with two control groups of 7 young Zucker lean rats (ZLR) and 8 Wistar Kyoto rats (WKY), respectively. Our goal is to broaden the characterization of glucose tolerance, including insulin secretion, in two animal models used for the characterization of human metabolic syndrome: the ZFR and the SHR. Reliable estimates of insulin sensitivity index, SI, was provided by minimal model analysis of IVGTT data. To characterize insulin secretion we calculated an index based on IVGTT data: AIRG, i.e. the acute insulin response after glucose bolus, related to the first phase insulin secretion. The ZFR showed a significantly (p<0.005) lower mean estimate of SI, and a significantly (p<0.001) higher mean value of AIRG, compared to control groups (ZLR and WKY) and hypertensive rats (SHR). Thus, only the ZFR shows a reduced insulin action, compensated only partially by insulin hypersecretion. This suggests obesity, with respect to hypertension, as a primary factor in the deterioration of glucose tolerance. © Springer International Publishing Switzerland 2016.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/236267 Collegamento a IRIS

2015
C-peptide-based assessment of insulin secretion in the Zucker fatty rat: A modelistic study
PLOS ONE
Autore/i: DI NARDO, Francesco; Cogo, Carla E.; Faelli, Emanuela; Morettini, Micaela; Burattini, Laura; Ruggeri, Piero
Classificazione: 1 Contributo su Rivista
Abstract: A C-peptide-based assessment of β-cell function was performed here in the Zucker fatty rat, a suitable animal model of human metabolic syndrome. To this aim, a 90-min intravenous glucose tolerance test (IVGTT) was performed in seven Zucker fatty rats (ZFR), 7-to-9week-old, and seven age-matched Zucker lean rats (ZLR). The minimal model of C-peptide (CPMM), originally introduced for humans, was adapted to Zucker rats and then applied to interpret IVGTT data. For a comprehensive evaluation of glucose tolerance in ZFR, CPMM was applied in combination with the minimal model of glucose kinetics (GKMM). Our results showed that the present CPMM-based interpretation of data is able to: 1) provide a suitable fit of C-Peptide data; 2) achieve a satisfactory estimation of parameters of interest 3) quantify both insulin secretion by estimating the time course of pre-hepatic secretion rate, SR(t), and total insulin secretion, TIS, and pancreatic sensitivity by means of three specific indexes of β-cell responsiveness to glucose stimulus (first-phase, φ1, second-phase, φ2, and steady-state, φsss, never assessed in Zucker rats before; 4) detect the significant enhancement of insulin secretion in the ZFR, in face of a severe insulin-resistant state, previously observed only using a purely experimental approach. Thus, the methodology presented here represents a reliable tool to assess β-cell function in the Zucker rat, and opens new possibilities for the quantification of further processes involved in glucose homeostasis such as the hepatic insulin degradation.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/228443 Collegamento a IRIS

2014
Preventing sudden cardiac death in sports: a novel monitoring service of the heart-rate variability trough wearable sensors
MBIDA - Proceedings of the International Workshop Mobile Networks for Biometric Data Analysis
Autore/i: Maranesi, Elvira; Morettini, Micaela; F., Palmieri; DI NARDO, Francesco; Burattini, Laura
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/205745 Collegamento a IRIS

2013
MATLAB-implemented estimation procedure for model-based assessment of hepatic insulin degradation from standard intravenous glucose tolerance test data
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
Autore/i: DI NARDO, Francesco; Michele, Mengoni; Morettini, Micaela
Classificazione: 1 Contributo su Rivista
Abstract: Present study provides a novel MATLAB-based parameter estimation procedure for individual assessment of hepatic insulin degradation (HID) process from standard frequently-sampled intravenous glucose tolerance test (FSIGTT) data. Direct access to the source code, offered by MATLAB, enabled us to design an optimization procedure based on the alternating use of Gauss-Newton’s and Levenberg-Marquardt’s algorithms, which assures the full convergence of the process and the containment of computational time.Reliability was tested by direct comparison with the application, in eighteen non-diabetic subjects, of well-known kinetic analysis software package SAAM II, and by application on different data. Agreement between MATLAB and SAAM II was warranted by intraclass correlation coefficients ≥0.73; no significant differences between corresponding mean parameter estimates and prediction of HID rate; and consistent residual analysis. Moreover, MATLAB optimization procedure resulted in a significant 51% reduction of CV% for the worst-estimated parameter by SAAM II and in maintaining all model-parameter CV% <20%. In conclusion, our MATLAB-based procedure was suggested as a suitable tool for the individual assessment of HID process.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/110875 Collegamento a IRIS

2013
The onset of type 2 diabetes: Proposal for a multi-scale model
JMIR. JOURNAL OF MEDICAL INTERNET RESEARCH
Autore/i: Castiglione, F.; Tieri, P.; De Graaf, A.; Franceschi, C.; Lio, P.; Van Ommen, B.; Mazza, C.; Tuchel, A.; Bernaschi, M.; Samson, C.; Colombo, T.; Castellani, G. C.; Capri, M.; Garagnani, P.; Salvioli, S.; Nguyen, V. A.; Bobeldijk-Pastorova, I.; Krishnan, S.; Cappozzo, A.; Sacchetti, M.; Morettini, M.; Ernst, M.
Classificazione: 1 Contributo su Rivista
Abstract: Background: Type 2 diabetes mellitus (T2D) is a common age-related disease, and is a major health concern, particularly in developed countries where the population is aging, including Europe. The multi-scale immune system simulator for the onset of type 2 diabetes (MISSION-T2D) is a European Union-funded project that aims to develop and validate an integrated, multilevel, and patient-specific model, incorporating genetic, metabolic, and nutritional data for the simulation and prediction of metabolic and inflammatory processes in the onset and progression of T2D. The project will ultimately provide a tool for diagnosis and clinical decision making that can estimate the risk of developing T2D and predict its progression in response to possible therapies. Recent data showed that T2D and its complications, specifically in the heart, kidney, retina, and feet, should be considered a systemic disease that is sustained by a pervasive, metabolically-driven state of inflammation. Accordingly, there is an urgent need (1) to understand the complex mechanisms underpinning the onset of this disease, and (2) to identify early patient-specific diagnostic parameters and related inflammatory indicators. Objective: We aim to accomplish this mission by setting up a multi-scale model to study the systemic interactions of the biological mechanisms involved in response to a variety of nutritional and metabolic stimuli and stressors. Methods: Specifically, we will be studying the biological mechanisms of immunological/inflammatory processes, energy intake/expenditure ratio, and cell cycle rate. The overall architecture of the model will exploit an already established immune system simulator as well as several discrete and continuous mathematical methods for modeling of the processes critically involved in the onset and progression of T2D. We aim to validate the predictions of our models using actual biological and clinical data. Results: This study was initiated in March 2013 and is expected to be completed by February 2016. Conclusions: MISSION-T2D aims to pave the way for translating validated multilevel immune-metabolic models into the clinical setting of T2D. This approach will eventually generate predictive biomarkers for this disease from the integration of clinical data with metabolic, nutritional, immune/inflammatory, genetic, and gut microbiota profiles. Eventually, it should prove possible to translate these into cost-effective and mobile-based diagnostic tools.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/273188 Collegamento a IRIS

2012
Mathematical model of standard oral glucose tolerance test for characterization of insulin potentiation in health
Autore/i: Morettini, Micaela
Editore: Università Politecnica delle Marche
Classificazione: 8 Tesi di dottorato
Abstract: In questo lavoro di tesi vengono proposte due diverse formulazioni (INT_M1 e INT_M2) di un nuovo modello integrato per la descrizione delle risposte del sistema di regolazione glucosio-insulina alla somministrazione orale di glucosio (oral glucose tolerance test, OGTT). INT_M1 e INT_M2 si differenziano per la descrizione dell’assorbimento gastrointestinale adottata: un modello ad un compartimento ed una funzione empirica per il primo ed un modello a tre compartimenti non lineare per il secondo. L’implementazione del modello in ambiente Matlab, all’interno di una nuova procedura di stima parametrica a due passi, ha permesso l’ottimizzazione di parametri caratteristici dell’assorbimento gastro-intestinale e della cinetica del glucosio, dell’insulina e dell’incretina. Il comportamento del modello è stato testato mediante best-fit di dati medi, presi dalla letteratura, delle concentrazioni plasmatiche di glucosio, insulina, di GIP (glucose-dependent insulinotropic polipeptide) e GLP-1 (glucagon-like peptide 1) misurati in due gruppi di soggetti sani (HC-1 e HC-2) sottoposti ad un protocollo OGTT standard e, successivamente, ad un protocollo endovenoso caratterizzato dalla somministrazione di un eguale andamento temporale del glucosio (isoglycemic intravenous glucose, I-IVG, infusion). I due modelli sono stati confrontati per quanto riguarda la capacità di riprodurre il potenziamento dell’insulina indotto dall’incretina ovvero l’aumentata risposta insulinica che si osserva a seguito di un OGTT paragonata a quella dell’I-IVG. Nell’ipotesi di un’azione additiva del GIP e del GLP-1 sul potenziamento dell’insulina, i risultati hanno mostrato una sostanziale equivalenza dei due modelli nel riprodurre i dati. Inoltre, i parametri stimati sembrano essere buoni indicatori delle differenze osservate nei due gruppi di soggetti sani. Infine la procedura di stima messa a punto apre la strada a future applicazioni mirate all’individualizzazione dell’effetto incretina.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/241987 Collegamento a IRIS

2011
Identification of an integrated mathematical model of standard oral glucose tolerance test for characterization of insulin potentiation in health
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
Autore/i: Burattini, Roberto; Morettini, M.
Classificazione: 1 Contributo su Rivista
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/59113 Collegamento a IRIS

2011
Incretin-induced insulin potentiation characterized by an improvedmathematical model of oral glucose tolerance test
IFMBE Proceedings
Autore/i: Morettini, M.; Guercio, G.; Burattini, Roberto
Editore: Springer
Luogo di pubblicazione: Berlin
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/62346 Collegamento a IRIS

2011
Dynamics of insulin action in hypertension: assessment from minimal model interpretation of intravenous glucose tolerance test data
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
Autore/i: Burattini, Roberto; Morettini, Micaela; DI NARDO, Francesco; Boemi, M.
Classificazione: 1 Contributo su Rivista
Abstract: Based on glucose kinetics minimal model (GKMM) interpretation of frequently sampled intravenous glucose tolerance test (FSIGTT), the aim was to broaden the characterization of insulin-mediated glucose disposal in hypertension by aid of a dynamic insulin sensitivity index, S-{\text{I}} {\text{D}}, and the related efficiency, η = S-{\text{I}}{\text{D}} /S-{\text{I}}, of the metabolic system to convert the maximal individual response capacity, measured by S I, into an effective insulin control on glucose. The C-peptide minimal model (CPMM) was used to interpret the role of β-cell function. Plasma glucose, insulin, and C-peptide concentrations were measured, during a 5-h FSIGTT, in eighteen normoglycemic individuals: ten hypertensive patients (H-group) and eight normotensive subjects (N-group) with no metabolic syndrome. Compared to our N-group, the H-group showed a significant (P < 0.05) reduction of both S I (56%) and S-{\text{I}}{\text{D}} (50%), no significant change of η, a significant increase of both the first-phase β-cell responsiveness to glucose (105%) and total insulin secretion (55%), and no significant change in disposition indexes, defined as the product of insulin sensitivity (either S I and S-{\text{I}}{\text{D}} ) and β-cell responsiveness. These findings suggest that, in spite of no change of efficiency, insulin resistance in normoglycemic hypertensive patients is primarily compensated by an increase in first-phase insulin secretion to preserve glucose tolerance to intravenous glucose load.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/56748 Collegamento a IRIS




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