Higher order spectra based support vector machine for arrhythmia classification

Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. HRV analysis is an important tool to observe the heart’s ability to respond to normal regulatory impulses that affect its rhythm. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. A computer-based arrhythmia detection system of cardiac states is very useful in diagnostics and disease management. In this work, we studied the identification of the HRV signals using features derived from HOS. These features were fed to the support vector machine (SVM) for classification. Our proposed system can classify the normal and other four classes of arrhythmia with an average accuracy of more than 85%.

Diminishment of respiratory sinus arrhythmia foreshadows doxorubicin-induced cardiomyopathy.

BACKGROUND: The development of a microcomputer-based device permits quick, simple, and noninvasive quantification of the respiratory sinus arrhythmia (RSA) during quiet breathing. METHODS AND RESULTS: We prospectively and serially measured the radionuclide left ventricular ejection fraction and the RSA amplitude in 34 cancer patients receiving up to nine monthly bolus treatments with doxorubicin hydrochloride (60 mg/m2). Of the eight patients who ultimately developed symptomatic doxorubicin-induced congestive heart failure, seven (87.5%) demonstrated a significant decline in RSA amplitude; five of 26 subjects without clinical symptoms of cardiotoxicity (19.2%) showed a similar RSA amplitude decline. On average, significant RSA amplitude decline occurred 3 months before the last planned doxorubicin dose in patients destined to develop clinical congestive heart failure. CONCLUSION: Overall, RSA amplitude abnormality proved to be a more specific predictor of clinically significant congestive heart failure than did serial resting radionuclide ejection fractions.

Predisposition to arrhythmia and autonomic dysfunction in Nhlh1-deficient mice.

Nhlh1 is a basic helix-loop-helix transcription factor whose expression is restricted to the nervous system and which may play a role in neuronal differentiation. To directly study Nhlh1 function, we generated null mice. Homozygous mutant mice were predisposed to premature, adult-onset, unexpected death. Electrocardiograms revealed decreased total heart rate variability, stress-induced arrhythmia, and impaired baroreceptor sensitivity. This predisposition to arrhythmia is a likely cause of the observed death in the mutant mice. Heterozygosity for the closely related transcription factor Nhlh2 increased the severity of the Nhlh1-null phenotype. No signs of primary cardiac structural or conduction abnormalities could be detected upon necropsy of the null mice. The pattern of altered heart rhythm observed in basal and experimental conditions (stress and pharmacologically induced) suggests that a deficient parasympathetic tone may contribute to the arrhythmia in the Nhlh1-null mouse. The expression of Nhlh1 in the developing brain stem and in the vagal nuclei in the wild-type mouse further supports this hypothesis. The Nhlh1 mutant mouse may thus provide a model to investigate the contribution of the autonomic nervous system to arrhythmogenesis.

Respiratory and non-respiratory sinus arrhythmia: implications for heart rate variability

The quantity of blood arriving at the left side of the heart oscillates throughout the breathing cycle due to the mechanics of breathing. Neurally regulated fluctuations in the length of the heart period act to dampen oscillations of the left ventricular stroke volume entering the aorta. We have reported that stroke volume oscillations but not spectral frequency variability stroke volume measures can be used to estimate the breathing frequency. This study investigated with the same recordings whether heart period oscillations or spectral heart rate variability measures could function as estimators of breathing frequency. Continuous 270 s cardiovascular recordings were obtained from 22 healthy adult volunteers in the supine and upright postures. Breathing was recorded simultaneously. Breathing frequency and heart period oscillation frequency were calculated manually, while heart rate variability spectral maximums were obtained using heart rate variability software. These estimates were compared to the breathing frequency using the Bland–Altman agreement procedure. Estimates were required to be \±10% (95% levels of agreement). The 95% levels of agreement measures for the heart period oscillation frequency (supine: -27.7 to 52.0%, upright: -37.8 to 45.9%) and the heart rate variability spectral maximum estimates (supine: -48.7 to 26.5% and -56.4 to 62.7%, upright: -37.8 to 39.3%) exceeded 10%. Multiple heart period oscillations were observed to occur during breathing cycles. Both respiratory and non-respiratory sinus arrhythmia was observed amongst healthy adults. This observation at least partly explains why heart period parameters and heart rate variability parameters are not reliable estimators of breathing frequency. In determining the validity of spectral heart rate variability measurements we suggest that it is the position of the spectral peaks and not the breathing

Ventricular arrhythmia in coronary artery disease: limits of a risk stratification strategy based on the ejection fraction alone and impact of infarct localization.

AIMS: Estimates of the left ventricular ejection fraction (LVEF) in patients with life-threatening ventricular arrhythmias related to coronary artery disease (CAD) have rarely been reported despite it has become the basis for determining patient's eligibility for prophylactic defibrillator. We aimed to determine the extent and distribution of reduced LVEF in patients with sustained ventricular tachycardia or ventricular fibrillation. METHODS AND RESULTS: 252 patients admitted for ventricular arrhythmia related to CAD were included: 149 had acute myocardial infarction (MI) (Group I, 59%), 54 had significant chronic obstructive CAD suggestive of an ischaemic arrhythmic trigger (Group II, 21%) and 49 patients had an old MI without residual ischaemia (Group III, 19%). 34% of the patients with scar-related arrhythmias had an LVEF > or =40%. Based on pre-event LVEF evaluation, it can be estimated that less than one quarter of the whole study population had a known chronic MI with severely reduced LVEF. In Group III, the proportion of inferior MI was significantly higher than anterior MI (81 vs. 19%; absolute difference, -62; 95% confidence interval, -45 to -79; P < or = 0.0001), though median LVEF was higher in inferior MI (0.37 +/- 10 vs. 0.29 +/- 10; P = 0.0499). CONCLUSION: Patients included in defibrillator trials represent only a minority of the patients at risk of sudden cardiac death. By applying the current risk stratification strategy based on LVEF, more than one third of the patients with old MI would not have qualified for a prophylactic defibrillator. Our study also suggests that inferior scars may be more prone to ventricular arrhythmia compared to anterior scars.

Respiratory Sinus Arrhythmia and Emotional Responding to Dyadic Discussions of a Disagreement as Predictors of Helping Related Subjective Well-Being in Older Mothers and Their Adult Daughters

The current study considered affect-related variables as predictors of the quality of helping relationships between older mothers and their adult daughters. Specifically, self-reported and observed emotional responses to the dyadic discussion of a disagreement between mothers and daughters, as well as baseline measures of respiratory sinus arrhythmia were considered as predictors of mothers' and daughters' satisfaction with their helping relationships. Relationship satisfaction was measured by considering mothers' and daughters' subjective well-being specifically in regards to the help they gave and received. Overall, these variables predicted more variance in mothers' satisfaction with their helping relationships than daughters', and RSA (respiratory sinus arrhythmia) was a stronger predictor than the self-reported or observed emotional reactions to the dyadic discussion of a disagreement. Implications of these findings and limitations to the current study are discussed.

The Role of MicroRNA Regulation of Cardiac Ion Channel in Arrhythmia

La fibrillation auriculaire (FA) est le trouble du rythme le plus fréquemment observé en pratique clinique. Elle constitue un risque important de morbi-mortalité. Le traitement de la FA reste un défi majeur en lien avec les nombreux effets secondaires associés aux approches thérapeutiques actuelles. Dans ce contexte, une meilleure compréhension des mécanismes sous-jacents à la FA est essentielle pour le développement de nouvelles thérapies offrant un meilleur rapport bénéfice/risque pour les patients. La FA est caractérisée par i) un remodelage électrique délétère associé le plus souvent ii) à un remodelage structurel du myocarde favorisant la récurrence et le maintien de l’arythmie. La diminution de la période réfractaire effective au sein du tissu auriculaire est un élément clef du remodelage électrique. Le remodelage structurel, quant à lui, se manifeste principalement par une fibrose tissulaire qui altère la propagation de l’influx électrique dans les oreillettes. Les mécanismes moléculaires impliqués dans la mise en place de ces deux substrats restent mal connus. Récemment, le rôle des microARNs (miARNs) a été pointé du doigt dans de nombreuses pathologies notamment cardiaques. Dans ce contexte les objectifs principaux de ce travail ont été i) d'acquérir une compréhension approfondie du rôle des miARNs dans la régulation de l’expression des canaux ioniques et ii) de mieux comprendre le rôle de ces molécules dans l’installation d’un substrat favorable a la FA. Nous avons, dans un premier temps, effectué une analyse bio-informatique combinée à des approches expérimentales spécifiques afin d’identifier clairement les miARNs démontrant un fort potentiel de régulation des gènes codant pour l’expression des canaux ioniques cardiaques humains. Nous avons identifié un nombre limité de miARNs cardiaques qui possédaient ces propriétés. Sur la base de ces résultats, nous avons démontré que l’altération de l'expression des canaux ioniques, observée dans diverse maladies cardiaques (par exemple, les cardiomyopathies, l’ischémie myocardique, et la fibrillation auriculaire), peut être soumise à ces miARNs suggérant leur implication dans l’arythmogénèse. La régulation du courant potassique IK1 est un facteur déterminant du remodelage électrique auriculaire associée à la FA. Les mécanismes moléculaires sous-jacents sont peu connus. Nous avons émis l’hypothèse que l'altération de l’expression des miARNs soit corrélée à l’augmentation de l’expression d’IK1 dans la FA. Nous avons constaté que l’expression de miR-26 est réduite dans la FA et qu’elle régule IK1 en modulant l’expression de sa sous-unité Kir2.1. Nous avons démontré que miR-26 est sous la répression transcriptionnelle du facteur nucléaire des lymphocytes T activés (NFAT) et que l’activité accrue de NFATc3/c4, aboutit à une expression réduite de miR-26. En conséquence IK1 augmente lors de la FA. Nous avons enfin démontré que l’interférence in vivo de miR-26 influence la susceptibilité à la FA en régulant IK1, confirmant le rôle prépondérant de miR-26 dans le remodelage auriculaire électrique. La fibrose auriculaire est un constituant majeur du remodelage structurel associé à la FA, impliquant l'activation des fibroblastes et l’influx cellulaire du Ca2 +. Nous avons cherché à déterminer i) si le canal perméable au Ca2+, TRPC3, jouait un rôle dans la fibrose auriculaire en favorisant l'activation des fibroblastes et ii) étudié le rôle potentiel des miARNs dans ce contexte. Nous avons démontré que les canaux TRPC3 favorisent l’influx du Ca2 +, activant la signalisation Ca2 +-dépendante ERK et en conséquence activent la prolifération des fibroblastes. Nous avons également démontré que l’expression du TRPC3 est augmentée dans la FA et que le blocage in vivo de TRPC3 empêche le développement de substrats reliés à la FA. Nous avons par ailleurs validé que miR-26 régule les canaux TRPC3 en diminuant leur expression dans les fibroblastes. Enfin, nous avons montré que l'expression réduite du miR-26 est également due à l’activité augmentée de NFATc3/c4 dans les fibroblastes, expliquant ainsi l’augmentation de TRPC3 lors de la FA, confirmant la contribution de miR-26 dans le processus de remodelage structurel lié à la FA. En conclusion, nos résultats mettent en évidence l'importance des miARNs dans la régulation des canaux ioniques cardiaques. Notamment, miR-26 joue un rôle important dans le remodelage électrique et structurel associé à la FA et ce, en régulant IK1 et l’expression du canal TRPC3. Notre étude démasque ainsi un mécanisme moléculaire de contrôle de la FA innovateur associant des miARNs. miR-26 en particulier représente apres ces travaux une nouvelle cible thérapeutique prometteuse pour traiter la FA.

Carbon monoxide induces cardiac arrhythmia via induction of the late Na+ current

Our data indicate that the proarrhythmic effects of CO arise from activation of NO synthase, leading to NO-mediated nitrosylation of Na(V)1.5 and to induction of the late Na(+) current. We also show that the antianginal drug ranolazine can abolish CO-induced early after-depolarizations, highlighting a novel approach to the treatment of CO-induced arrhythmias.

Individualized arrhythmia detection with ECG signals from wearable devices

Low cost pervasive electrocardiogram (ECG) monitors is changing how sinus arrhythmia are diagnosed among patients with mild symptoms. With the large amount of data generated from long-term monitoring, come new data science and analytical challenges. Although traditional rule-based detection algorithms still work on relatively short clinical quality ECG, they are not optimal for pervasive signals collected from wearable devices - they don't adapt to individual difference and assume accurate identification of ECG fiducial points. To overcome these short-comings of the rule-based methods, this paper introduces an arrhythmia detection approach for low quality pervasive ECG signals. To achieve the robustness needed, two techniques were applied. First, a set of ECG features with minimal reliance on fiducial point identification were selected. Next, the features were normalized using robust statistics to factors out baseline individual differences and clinically irrelevant temporal drift that is common in pervasive ECG. The proposed method was evaluated using pervasive ECG signals we collected, in combination with clinician validated ECG signals from Physiobank. Empirical evaluation confirms accuracy improvements of the proposed approach over the traditional clinical rules.

Digitalis-Like Induced Arrhythmia in a Patient with Rheumatic Mitral Regurgitation Complicated by Preeclampsia

Objective. To report a case of cardiac arrhythmia related to a low dose of endovenous lanatoside C. Case report. A 23-year-old pregnant woman with mitral regurgitation complicated with preeclampsia and pulmonary edema presented 2 episodes of atrial tachycardia induced by a intravenous digitalis (2 mg, IV and 1 mg, IV, respectively). Conclusion. This case calls attention to the need for further studies analysing the security of digoxin use in preeclampsia.

Evidence for a respiratory component, similar to mammalian respiratory sinus arrhythmia, in the heart rate variability signal from the rattlesnake, Crotalus durissus terrificus

Autonomic control of heart rate variability and the central location of vagal preganglionic neurones (VPN) were examined in the rattlesnake ( Crotalus durissus terrificus), in order to determine whether respiratory sinus arrhythmia (RSA) occurred in a similar manner to that described for mammals. Resting ECG signals were recorded in undisturbed snakes using miniature datalogging devices, and the presence of oscillations in heart rate (f(H)) was assessed by power spectral analysis (PSA). This mathematical technique provides a graphical output that enables the estimation of cardiac autonomic control by measuring periodic changes in the heart beat interval. At fH above 19 min(-1) spectra were mainly characterised by low frequency components, reflecting mainly adrenergic tonus on the heart. By contrast, at f(H) below 19 min(-1) spectra typically contained high frequency components, demonstrated to be cholinergic in origin. Snakes with a f(H) > 19 min(-1) may therefore have insufficient cholinergic tonus and/or too high an adrenergic tonus acting upon the heart for respiratory sinus arrhythmia ( RSA) to develop. A parallel study monitored f(Hd) simultaneously with the intraperitoneal pressures associated with lung inflation. Snakes with a fH < 19 min(-1) exhibited a high frequency (HF) peak in the power spectrum, which correlated with ventilation rate (f(V)). Adrenergic blockade by propranolol infusion increased the variability of the ventilation cycle, and the oscillatory component of the f(H) spectrum broadened accordingly. Infusion of atropine to effect cholinergic blockade abolished this HF component, confirming a role for vagal control of the heart in matching f(H) and f(V) in the rattlesnake. A neuroanatomical study of the brainstem revealed two locations for vagal preganglionic neurones (VPN). This is consistent with the suggestion that generation of ventilatory components in the heart rate variability (HRV) signal are dependent on spatially distinct loci for cardiac VPN. Therefore, this study has demonstrated the presence of RSA in the HRV signal and a dual location for VPN in the rattlesnake. We suggest there to be a causal relationship between these two observations.

ECG arrhythmia classification based on optimum-path forest

An important tool for the heart disease diagnosis is the analysis of electrocardiogram (ECG) signals, since the non-invasive nature and simplicity of the ECG exam. According to the application, ECG data analysis consists of steps such as preprocessing, segmentation, feature extraction and classification aiming to detect cardiac arrhythmias (i.e.; cardiac rhythm abnormalities). Aiming to made a fast and accurate cardiac arrhythmia signal classification process, we apply and analyze a recent and robust supervised graph-based pattern recognition technique, the optimum-path forest (OPF) classifier. To the best of our knowledge, it is the first time that OPF classifier is used to the ECG heartbeat signal classification task. We then compare the performance (in terms of training and testing time, accuracy, specificity, and sensitivity) of the OPF classifier to the ones of other three well-known expert system classifiers, i.e.; support vector machine (SVM), Bayesian and multilayer artificial neural network (MLP), using features extracted from six main approaches considered in literature for ECG arrhythmia analysis. In our experiments, we use the MIT-BIH Arrhythmia Database and the evaluation protocol recommended by The Association for the Advancement of Medical Instrumentation. A discussion on the obtained results shows that OPF classifier presents a robust performance, i.e.; there is no need for parameter setup, as well as a high accuracy at an extremely low computational cost. Moreover, in average, the OPF classifier yielded greater performance than the MLP and SVM classifiers in terms of classification time and accuracy, and to produce quite similar performance to the Bayesian classifier, showing to be a promising technique for ECG signal analysis. © 2012 Elsevier Ltd. All rights reserved.

A Phase Space Box-counting based Method for Arrhythmia Prediction from Electrocardiogram Time Series

Arrhythmia is one kind of cardiovascular diseases that give rise to the number of deaths and potentially yields immedicable danger. Arrhythmia is a life threatening condition originating from disorganized propagation of electrical signals in heart resulting in desynchronization among different chambers of the heart. Fundamentally, the synchronization process means that the phase relationship of electrical activities between the chambers remains coherent, maintaining a constant phase difference over time. If desynchronization occurs due to arrhythmia, the coherent phase relationship breaks down resulting in chaotic rhythm affecting the regular pumping mechanism of heart. This phenomenon was explored by using the phase space reconstruction technique which is a standard analysis technique of time series data generated from nonlinear dynamical system. In this project a novel index is presented for predicting the onset of ventricular arrhythmias. Analysis of continuously captured long-term ECG data recordings was conducted up to the onset of arrhythmia by the phase space reconstruction method, obtaining 2-dimensional images, analysed by the box counting method. The method was tested using the ECG data set of three different kinds including normal (NR), Ventricular Tachycardia (VT), Ventricular Fibrillation (VF), extracted from the Physionet ECG database. Statistical measures like mean (μ), standard deviation (σ) and coefficient of variation (σ/μ) for the box-counting in phase space diagrams are derived for a sliding window of 10 beats of ECG signal. From the results of these statistical analyses, a threshold was derived as an upper bound of Coefficient of Variation (CV) for box-counting of ECG phase portraits which is capable of reliably predicting the impeding arrhythmia long before its actual occurrence. As future work of research, it was planned to validate this prediction tool over a wider population of patients affected by different kind of arrhythmia, like atrial fibrillation, bundle and brunch block, and set different thresholds for them, in order to confirm its clinical applicability.

Seasonal variations of ventricular arrhythmia clusters in defibrillator recipients

BACKGROUND: Clustering ventricular arrhythmias are the consequence of acute ventricular electrical instability and represent a challenge in the management of the growing number of patients with an implantable cardioverter-defibrillator (ICD). Triggering factors can rarely be identified. OBJECTIVES: Several studies have revealed seasonal variations in the frequency of cardiovascular events and life-threatening arrhythmias, and we sought to establish whether seasonal factors may exacerbate ventricular electrical instability leading to arrhythmia clusters and electrical storm. METHODS: Two hundred and fourteen consecutive defibrillator recipients were followed-up during 3.3 +/- 2.2 years. Arrhythmia cluster was defined as the occurrence of three or more arrhythmic events triggering appropriate defibrillator therapies within 2 weeks. Time intervals between two clusters were calculated for each month and each season, and were compared using Kruskal-Wallis test and Wilcoxon-Mann-Whitney test with Bonferroni adjustment. RESULTS: During a follow-up of 698 patient years, 98 arrhythmia clusters were observed in 51 patients; clustering ventricular arrhythmias were associated with temporal variables; they occurred more frequently in the winter and spring months than during the summer and fall. Accordingly, the time intervals between two clusters were significantly shorter during winter and spring (median and 95% CI): winter 16 (5-19), spring 11.5 (7-25), summer 34.5 (15-55), fall 50.5 (19-65), P = 0.0041. CONCLUSION: There are important seasonal variations in the incidence of arrhythmia clusters in ICD recipients. Whether these variations are related to environmental factors, change in physical activity, or psychological factors requires further study.