Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology, 2016
An in-depth examination of the cutting edge of biometrics This book fills a gap in the literature... more An in-depth examination of the cutting edge of biometrics This book fills a gap in the literature by detailing the recent advances and emerging theories, methods, and applications of biometric systems in a variety of infrastructures. Edited by a panel of experts, it provides comprehensive coverage of: Multilinear discriminant analysis for biometric signal recognition Biometric identity authentication techniques based on neural networks Multimodal biometrics and design of classifiers for biometric fusion Feature selection and ...
Expanded into two volumes, the Second Edition of Springer&amp... more Expanded into two volumes, the Second Edition of Springer's Encyclopedia of Cryptography and Security brings the latest and most comprehensive coverage of the topic: Definitive information on cryptography and information security from highly regarded researchers Effective tool for professionals in many fields and researchers of all levels Extensive resource with more than 700 contributions in Second Edition 5643 references, more than twice the number of references that appear in the First Edition With over 300 new entries, ...
Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology, Jan 14, 2015
Following the publication of the Task Force document on heart rate variability (HRV) in 1996, a n... more Following the publication of the Task Force document on heart rate variability (HRV) in 1996, a number of articles have been published to describe new HRV methodologies and their application in different physiological and clinical studies. This document presents a critical review of the new methods. A particular attention has been paid to methodologies that have not been reported in the 1996 standardization document but have been more recently tested in sufficiently sized populations. The following methods were considered: Long-range correlation and fractal analysis; Short-term complexity; Entropy and regularity; and Nonlinear dynamical systems and chaotic behaviour. For each of these methods, technical aspects, clinical achievements, and suggestions for clinical application were reviewed. While the novel approaches have contributed in the technical understanding of the signal character of HRV, their success in developing new clinical tools, such as those for the identification of h...
The V-index is an ECG marker quantifying spatial heterogeneity of ventricular repolarization. We ... more The V-index is an ECG marker quantifying spatial heterogeneity of ventricular repolarization. We prospectively assessed the diagnostic and prognostic values of the V-index in patients with suspected non-ST-elevation myocardial infarction (NSTEMI). We prospectively enrolled 497 patients presenting with suspected NSTEMI to the emergency department (ED). Digital 12-lead ECGs of five-minute duration were recorded at presentation. The V-index was automatically calculated in a blinded fashion. Patients with a QRS duration >120ms were ruled out from analysis. The final diagnosis was adjudicated by two independent cardiologists. The prognostic endpoint was all-cause mortality during 24months of follow-up. NSTEMI was the final diagnosis in 14% of patients. V-index levels were higher in patients with AMI compared to other causes of chest pain (median 23ms vs. 18ms, p<0.001). The use of the V-index in addition to conventional ECG-criteria improved the diagnostic accuracy for the diagnosi...
2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015
Falling in elderly is a worldwide major problem because it can lead to severe injuries, and even ... more Falling in elderly is a worldwide major problem because it can lead to severe injuries, and even sudden death. Fall risk prediction would provide rapid intervention, as well as reducing the over burden of healthcare systems. Such prediction is currently performed by means of clinical scales. Among them, the Tinetti Scale is one of the better established and mostly used in clinical practice. In this work, we proposed an automatic method to assess the Tinetti scores using a wearable accelerometer. The balance and gait characteristics of 13 elderly subjects have been scored by an expert clinician while performing 8 different motor tasks according to the Tinetti Scale protocol. Two statistical analysis were selected. First, a linear regression study was performed between the Tinetti scores and 8 features (one feature for each task). Second, the generalization quality of the regression model was assessed using a Leave-One SubjectOut approach. The multiple linear regression provided a high correlation between the Tinetti scores and the features proposed (adj. R(2) = 0.948; p = 0.003). Moreover, six of the eight features added statistically significantly to the prediction of the scores (p &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;; 0.05). When testing the generalization capability of the model, a moderate linear correlation was obtained (R(2) = 0.67; p &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;; 0.05). The results suggested that the automatic method might be a promising tool to assess the falling risk of older individuals.
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2006
The purpose of this work is to characterize the heart rate variability (HRV) of patients affected... more The purpose of this work is to characterize the heart rate variability (HRV) of patients affected by congestive heart failure (CHF) and to find out the main difference between this pathological condition and the physiological state. Parameters adopted in this work are: the detrended fluctuation analysis (DFA) and the Higuchi exponent to assess long correlations and self-similarity; the regularity estimators, approximate entropy (ApEn) and sample entropy (SampEn) and the multiscale entropy (MSE). Furthermore we proposed a new regularity index, the Gaussian entropy (GaussEn) which is a modification of the previous ApEn and SampEn. The results show the proposed parameters do an effective separation of physiological and pathological subject conditions. These results are part of a study evaluating the nonlinear index prognostic value toward cardiac death.
European Journal of Obstetrics & Gynecology and Reproductive Biology, 2015
Intrauterine growth restriction (IUGR) is characterized by chronic nutrient deprivation and hypox... more Intrauterine growth restriction (IUGR) is characterized by chronic nutrient deprivation and hypoxemia that alters the autonomous nervous system regulation of fetal heart rate variability (fHRV). Phase-rectified signal averaging (PRSA) is a new algorithm capable to identify periodic and quasi-periodic patterns of HR, and which is used to quantify the average acceleration and deceleration capacity (AC/DC) of the heart. The computation of AC/DC depends on the parameters T and s, which we set so that s=T. T and s determine the periodicities that can be detected (the larger T the smaller the frequency of oscillations for which the method is most sensitive). The aim of the study was to evaluate the influence of the parameter T on PRSA computation, based on trans-abdominally acquired fetal ECG (ta-fECG), in early IUGR (&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;34 weeks of gestation) at two different gestational age epochs. AC/DC were calculated for different T values (1÷45) on fetal RR intervals derived from ta-fECG in 22 IUGR and in 37 appropriate for gestational age (AGA) fetuses matched for gestational age, in two gestational age epochs: very preterm group (≥26÷&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;30 weeks), and preterm group (≥30÷&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;34 weeks), respectively. AC/DC were significantly lower in IUGR than in AGA fetuses for all T≥5 values (p&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;0.05). The best area under the receiver operating characteristic curve (AUC) in identifying IUGR at time of recording was observed for T9 [AUC AC-T9 0.87, 95% confidence interval (CI) 0.77-0.96; and AUC DC-T9 0.89, 95% CI 0.81-0.98), and in range of T 7÷15. In the same T interval, AC/DC were significantly lower in very preterm than in preterm IUGR group (p&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;0.05), while there were no differences in AGA fetuses at two gestational age epochs (p&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;0.05), respectively. The AUCs of AC-T9 and DC-T9 significantly outperformed that obtained by short-term variation (AUC 0.77, 95% CI 0.65-0.90; p=0.009 and p=0.003, respectively). Our study shows that within the range of T parameter 1÷45, T=9 proved to be the best value to discriminate the AC and DC of the fetal heart rate of IUGR from AGA fetuses prior to 34 weeks of gestation. These significant differences are emphasized in very preterm gestational age epochs.
Medical & Biological Engineering & Computing, 2015
The work considers automatic sleep stage classification, based on heart rate variability (HRV) an... more The work considers automatic sleep stage classification, based on heart rate variability (HRV) analysis, with a focus on the distinction of wakefulness (WAKE) from sleep and rapid eye movement (REM) from non-REM (NREM) sleep. A set of 20 automatically annotated one-night polysomnographic recordings was considered, and artificial neural networks were selected for classification. For each inter-heartbeat (RR) series, beside features previously presented in literature, we introduced a set of four parameters related to signal regularity. RR series of three different lengths were considered (corresponding to 2, 6, and 10 successive epochs, 30 s each, in the same sleep stage). Two sets of only four features captured 99 % of the data variance in each classification problem, and both of them contained one of the new regularity features proposed. The accuracy of classification for REM versus NREM (68.4 %, 2 epochs; 83.8 %, 10 epochs) was higher than when distinguishing WAKE versus SLEEP (67.6 %, 2 epochs; 71.3 %, 10 epochs). Also, the reliability parameter (Cohens&#39;s Kappa) was higher (0.68 and 0.45, respectively). Sleep staging classification based on HRV was still less precise than other staging methods, employing a larger variety of signals collected during polysomnographic studies. However, cheap and unobtrusive HRV-only sleep classification proved sufficiently precise for a wide range of applications.
ABSTRACT Enhanced temporal variability of ventricular repolarization has been related to increase... more ABSTRACT Enhanced temporal variability of ventricular repolarization has been related to increased ventricular arrhythmic risk. In this study, we investigate the influence of stochastic ion channel gating on the variability of four arrhythmic risk biomarkers: action potential (AP) duration (APD), AP triangulation and systolic and diastolic calcium levels. Different levels of white noise, representing different channel numbers, were introduced by means of a stochastic differential equation for the gating variables of the ten Tusscher-Panfilov human ventricular model (TP06). In single cells the rapid and slow delayed rectifier potassium currents (IKr and IKs) were the main contributors to biomarkers variability, which was shown to be increased at fast pacing frequencies, particularly for APD and diastolic calcium. At tissue level, electrotonic coupling masked the effects of stochastic gating on the variability of all the investigated biomarkers. In particular, a very notable reduction in variability was obtained for 2D and 3D tissue models, with 80% reduction with respect to 1D models, and more than 20 folds with respect to isolated cells under physiological conditions. This indicates that large variations in cellular AP are required in order to reproduce physiological variability levels measured in tissue.
ABSTRACT A physiological spatial heterogeneity of ventricular repolarization (SHVR) is responsibl... more ABSTRACT A physiological spatial heterogeneity of ventricular repolarization (SHVR) is responsible for the T-wave on the ECG. However, an increased SHVR might favor the development of ventricular arrhythmias. The ν-index is a metric introduced with the aim of assessing SHVR from ECG.
Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology, 2016
An in-depth examination of the cutting edge of biometrics This book fills a gap in the literature... more An in-depth examination of the cutting edge of biometrics This book fills a gap in the literature by detailing the recent advances and emerging theories, methods, and applications of biometric systems in a variety of infrastructures. Edited by a panel of experts, it provides comprehensive coverage of: Multilinear discriminant analysis for biometric signal recognition Biometric identity authentication techniques based on neural networks Multimodal biometrics and design of classifiers for biometric fusion Feature selection and ...
Expanded into two volumes, the Second Edition of Springer&amp;amp;amp;amp;amp;amp;amp;amp;amp... more Expanded into two volumes, the Second Edition of Springer&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;#x27;s Encyclopedia of Cryptography and Security brings the latest and most comprehensive coverage of the topic: Definitive information on cryptography and information security from highly regarded researchers Effective tool for professionals in many fields and researchers of all levels Extensive resource with more than 700 contributions in Second Edition 5643 references, more than twice the number of references that appear in the First Edition With over 300 new entries, ...
Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology, Jan 14, 2015
Following the publication of the Task Force document on heart rate variability (HRV) in 1996, a n... more Following the publication of the Task Force document on heart rate variability (HRV) in 1996, a number of articles have been published to describe new HRV methodologies and their application in different physiological and clinical studies. This document presents a critical review of the new methods. A particular attention has been paid to methodologies that have not been reported in the 1996 standardization document but have been more recently tested in sufficiently sized populations. The following methods were considered: Long-range correlation and fractal analysis; Short-term complexity; Entropy and regularity; and Nonlinear dynamical systems and chaotic behaviour. For each of these methods, technical aspects, clinical achievements, and suggestions for clinical application were reviewed. While the novel approaches have contributed in the technical understanding of the signal character of HRV, their success in developing new clinical tools, such as those for the identification of h...
The V-index is an ECG marker quantifying spatial heterogeneity of ventricular repolarization. We ... more The V-index is an ECG marker quantifying spatial heterogeneity of ventricular repolarization. We prospectively assessed the diagnostic and prognostic values of the V-index in patients with suspected non-ST-elevation myocardial infarction (NSTEMI). We prospectively enrolled 497 patients presenting with suspected NSTEMI to the emergency department (ED). Digital 12-lead ECGs of five-minute duration were recorded at presentation. The V-index was automatically calculated in a blinded fashion. Patients with a QRS duration >120ms were ruled out from analysis. The final diagnosis was adjudicated by two independent cardiologists. The prognostic endpoint was all-cause mortality during 24months of follow-up. NSTEMI was the final diagnosis in 14% of patients. V-index levels were higher in patients with AMI compared to other causes of chest pain (median 23ms vs. 18ms, p<0.001). The use of the V-index in addition to conventional ECG-criteria improved the diagnostic accuracy for the diagnosi...
2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015
Falling in elderly is a worldwide major problem because it can lead to severe injuries, and even ... more Falling in elderly is a worldwide major problem because it can lead to severe injuries, and even sudden death. Fall risk prediction would provide rapid intervention, as well as reducing the over burden of healthcare systems. Such prediction is currently performed by means of clinical scales. Among them, the Tinetti Scale is one of the better established and mostly used in clinical practice. In this work, we proposed an automatic method to assess the Tinetti scores using a wearable accelerometer. The balance and gait characteristics of 13 elderly subjects have been scored by an expert clinician while performing 8 different motor tasks according to the Tinetti Scale protocol. Two statistical analysis were selected. First, a linear regression study was performed between the Tinetti scores and 8 features (one feature for each task). Second, the generalization quality of the regression model was assessed using a Leave-One SubjectOut approach. The multiple linear regression provided a high correlation between the Tinetti scores and the features proposed (adj. R(2) = 0.948; p = 0.003). Moreover, six of the eight features added statistically significantly to the prediction of the scores (p &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;; 0.05). When testing the generalization capability of the model, a moderate linear correlation was obtained (R(2) = 0.67; p &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;; 0.05). The results suggested that the automatic method might be a promising tool to assess the falling risk of older individuals.
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2006
The purpose of this work is to characterize the heart rate variability (HRV) of patients affected... more The purpose of this work is to characterize the heart rate variability (HRV) of patients affected by congestive heart failure (CHF) and to find out the main difference between this pathological condition and the physiological state. Parameters adopted in this work are: the detrended fluctuation analysis (DFA) and the Higuchi exponent to assess long correlations and self-similarity; the regularity estimators, approximate entropy (ApEn) and sample entropy (SampEn) and the multiscale entropy (MSE). Furthermore we proposed a new regularity index, the Gaussian entropy (GaussEn) which is a modification of the previous ApEn and SampEn. The results show the proposed parameters do an effective separation of physiological and pathological subject conditions. These results are part of a study evaluating the nonlinear index prognostic value toward cardiac death.
European Journal of Obstetrics & Gynecology and Reproductive Biology, 2015
Intrauterine growth restriction (IUGR) is characterized by chronic nutrient deprivation and hypox... more Intrauterine growth restriction (IUGR) is characterized by chronic nutrient deprivation and hypoxemia that alters the autonomous nervous system regulation of fetal heart rate variability (fHRV). Phase-rectified signal averaging (PRSA) is a new algorithm capable to identify periodic and quasi-periodic patterns of HR, and which is used to quantify the average acceleration and deceleration capacity (AC/DC) of the heart. The computation of AC/DC depends on the parameters T and s, which we set so that s=T. T and s determine the periodicities that can be detected (the larger T the smaller the frequency of oscillations for which the method is most sensitive). The aim of the study was to evaluate the influence of the parameter T on PRSA computation, based on trans-abdominally acquired fetal ECG (ta-fECG), in early IUGR (&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;34 weeks of gestation) at two different gestational age epochs. AC/DC were calculated for different T values (1÷45) on fetal RR intervals derived from ta-fECG in 22 IUGR and in 37 appropriate for gestational age (AGA) fetuses matched for gestational age, in two gestational age epochs: very preterm group (≥26÷&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;30 weeks), and preterm group (≥30÷&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;34 weeks), respectively. AC/DC were significantly lower in IUGR than in AGA fetuses for all T≥5 values (p&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;0.05). The best area under the receiver operating characteristic curve (AUC) in identifying IUGR at time of recording was observed for T9 [AUC AC-T9 0.87, 95% confidence interval (CI) 0.77-0.96; and AUC DC-T9 0.89, 95% CI 0.81-0.98), and in range of T 7÷15. In the same T interval, AC/DC were significantly lower in very preterm than in preterm IUGR group (p&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;lt;0.05), while there were no differences in AGA fetuses at two gestational age epochs (p&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;gt;0.05), respectively. The AUCs of AC-T9 and DC-T9 significantly outperformed that obtained by short-term variation (AUC 0.77, 95% CI 0.65-0.90; p=0.009 and p=0.003, respectively). Our study shows that within the range of T parameter 1÷45, T=9 proved to be the best value to discriminate the AC and DC of the fetal heart rate of IUGR from AGA fetuses prior to 34 weeks of gestation. These significant differences are emphasized in very preterm gestational age epochs.
Medical & Biological Engineering & Computing, 2015
The work considers automatic sleep stage classification, based on heart rate variability (HRV) an... more The work considers automatic sleep stage classification, based on heart rate variability (HRV) analysis, with a focus on the distinction of wakefulness (WAKE) from sleep and rapid eye movement (REM) from non-REM (NREM) sleep. A set of 20 automatically annotated one-night polysomnographic recordings was considered, and artificial neural networks were selected for classification. For each inter-heartbeat (RR) series, beside features previously presented in literature, we introduced a set of four parameters related to signal regularity. RR series of three different lengths were considered (corresponding to 2, 6, and 10 successive epochs, 30 s each, in the same sleep stage). Two sets of only four features captured 99 % of the data variance in each classification problem, and both of them contained one of the new regularity features proposed. The accuracy of classification for REM versus NREM (68.4 %, 2 epochs; 83.8 %, 10 epochs) was higher than when distinguishing WAKE versus SLEEP (67.6 %, 2 epochs; 71.3 %, 10 epochs). Also, the reliability parameter (Cohens&#39;s Kappa) was higher (0.68 and 0.45, respectively). Sleep staging classification based on HRV was still less precise than other staging methods, employing a larger variety of signals collected during polysomnographic studies. However, cheap and unobtrusive HRV-only sleep classification proved sufficiently precise for a wide range of applications.
ABSTRACT Enhanced temporal variability of ventricular repolarization has been related to increase... more ABSTRACT Enhanced temporal variability of ventricular repolarization has been related to increased ventricular arrhythmic risk. In this study, we investigate the influence of stochastic ion channel gating on the variability of four arrhythmic risk biomarkers: action potential (AP) duration (APD), AP triangulation and systolic and diastolic calcium levels. Different levels of white noise, representing different channel numbers, were introduced by means of a stochastic differential equation for the gating variables of the ten Tusscher-Panfilov human ventricular model (TP06). In single cells the rapid and slow delayed rectifier potassium currents (IKr and IKs) were the main contributors to biomarkers variability, which was shown to be increased at fast pacing frequencies, particularly for APD and diastolic calcium. At tissue level, electrotonic coupling masked the effects of stochastic gating on the variability of all the investigated biomarkers. In particular, a very notable reduction in variability was obtained for 2D and 3D tissue models, with 80% reduction with respect to 1D models, and more than 20 folds with respect to isolated cells under physiological conditions. This indicates that large variations in cellular AP are required in order to reproduce physiological variability levels measured in tissue.
ABSTRACT A physiological spatial heterogeneity of ventricular repolarization (SHVR) is responsibl... more ABSTRACT A physiological spatial heterogeneity of ventricular repolarization (SHVR) is responsible for the T-wave on the ECG. However, an increased SHVR might favor the development of ventricular arrhythmias. The ν-index is a metric introduced with the aim of assessing SHVR from ECG.
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