Dimensional analysis of HRV in hypertrophic cardiomyopathy patients

On Entropy of Probability Integral Transformed Time Series

The goal of this paper is to investigate the changes of entropy estimates when the amplitude distribution of the time series is equalized using the probability integral transformation. The data we analyzed were with known properties-pseudo-random signals with known distributions, mutually coupled using statistical or deterministic methods that include generators of statistically dependent distributions, linear and non-linear transforms, and deterministic chaos. The signal pairs were coupled using a correlation coefficient ranging from zero to one. The dependence of the signal samples is achieved by moving average filter and non-linear equations. The applied coupling methods are checked using statistical tests for correlation. The changes in signal regularity are checked by a multifractal spectrum. The probability integral transformation is then applied to cardiovascular time series-systolic blood pressure and pulse interval-acquired from the laboratory animals and represented the results of entropy estimations. We derived an expression for the reference value of entropy in the probability integral transformed signals. We also experimentally evaluated the reliability of entropy estimates concerning the matching probabilities.

Prediction of Sudden Cardiac Death in Implantable Cardioverter Defibrillators: A Review and Comparative Study of Heart Rate Variability Features

Over the last four decades, implantable cardioverter defibrillators (ICDs) have been widely deployed to reduce sudden cardiac death (SCD) risk in patients with a history of life-threatening arrhythmia. By continuous monitoring of the heart rate, ICDs can use decision algorithms to distinguish normal cardiac sinus rhythm or supra-ventricular tachycardia from abnormal cardiac rhythms like ventricular tachycardia and ventricular fibrillation and deliver appropriate therapy such as an electrical stimulus. Despite the success of ICDs, more research is still needed, particularly in decision-making algorithms. Because of low specificity in practical devices, patients with ICDs still receive inappropriate shocks, which may lead to inadvertent mortality and reduction of quality of life. At the same time, higher sensitivity can lead to the use of newer tiered therapies. The purpose of this study is to review the literature on common signal features used in detection algorithms for abnormal cardiac sinus rhythm, as well as reviewing datasets used for algorithm development in previous studies. More than 50 different features to address heart rate changes before SCD have been reviewed and general methodology on this area proposed based on variety of studies on ICDs functionality. A comparative study on the prediction performance of these features, using a common database, is also presented. By combining these features with a support vector machine classifier, achieved results have compared well with other studies.

Binarized cross-approximate entropy in crowdsensing environment

OBJECTIVES

Personalised monitoring in health applications has been recognised as part of the mobile crowdsensing concept, where subjects equipped with sensors extract information and share them for personal or common benefit. Limited transmission resources impose the use of local analyses methodology, but this approach is incompatible with analytical tools that require stationary and artefact-free data. This paper proposes a computationally efficient binarised cross-approximate entropy, referred to as (X)BinEn, for unsupervised cardiovascular signal processing in environments where energy and processor resources are limited.

METHODS

The proposed method is a descendant of the cross-approximate entropy ((X)ApEn). It operates on binary, differentially encoded data series split into m-sized vectors. The Hamming distance is used as a distance measure, while a search for similarities is performed on the vector sets. The procedure is tested on rats under shaker and restraint stress, and compared to the existing (X)ApEn results.

RESULTS

The number of processing operations is reduced. (X)BinEn captures entropy changes in a similar manner to (X)ApEn. The coding coarseness yields an adverse effect of reduced sensitivity, but it attenuates parameter inconsistency and binary bias. A special case of (X)BinEn is equivalent to Shannon's entropy. A binary conditional entropy for m =1 vectors is embedded into the (X)BinEn procedure.

CONCLUSION

(X)BinEn can be applied to a single time series as an auto-entropy method, or to a pair of time series, as a cross-entropy method. Its low processing requirements makes it suitable for mobile, battery operated, self-attached sensing devices, with limited power and processor resources.

Multipole analysis of heart rate variability as a predictor of imminent ventricular arrhythmias in ICD patients

BACKGROUND

Contemporary implantable cardiac defibrillators (ICD) enable storage of multiple, preepisode R-R recordings in patients who suffered from ventricular tachyarrhythmia (VTA). Timely prediction of VTA, using heart rate variability (HRV) analysis techniques, may facilitate the implementation of preventive and therapeutic strategies.

AIM

To evaluate the novel multipole method of the HRV analysis in prediction of imminent VTAs in ICD patients.

METHODS

We screened patients from the Biotronik HAWAI Registry (Heart Rate Analysis with Automated ICDs). A total of 28 patients from the HAWAI registries (phase I and II), having medical records, who had experienced documented, verified VTA during the 2-year follow-up, were included in our analysis. HRV during preepisode recordings of 4,500 R-R intervals were analyzed using the Dyx parameter and compared to HRV of similar length recordings from the same patients that were not followed by arrhythmia.

RESULTS

Our study population consisted mainly of men 25 of 28 (89%), average age of 64.8 ± 9.4 years, 92% with coronary artery disease. HRV during 64 preevent recordings (2.3 events per patient on average) was analyzed and compared with 60 control recordings. The multipole method of HRV analysis showed 50% sensitivity and 91.6% specificity for prediction of ventricular tachycardia/ventricular fibrillation in the study population, with 84.5% positive predictive value. No statistically significant correlation was found between various clinical parameters and the sensitivity of imminent VTA predetection in our patients.

CONCLUSION

The multipole method of HRV analysis emerges as a highly specific, possible predictor of imminent VTA, providing an early warning allowing to prepare for an arrhythmic episode.

Unbiased entropy estimates in stress: a parameter study

This study proposes a method for obtaining a stable working point that enables the unbiased estimates of the approximate entropy and the sample entropy. Pattern length, normalized threshold, time delay and tines series length are levels of freedom that are considered. Pulse interval signals used for the experiment are recorded from laboratory animals with different likelihood of developing cardiovascular disease--normal and borderline hypertensive rats--exposed to the acute and to the chronic stress. It is shown that the threshold level is the major source of the instability, and that the generally accepted and widely used methods for a threshold choice may lead to an incorrect psychological interpretation. A method for the threshold level correction is proposed.

Environmental stress: approximate entropy approach revisited

Radiotelemetred male Wistar outbrad rats and Borderline Hypertensive rats (BHR) were exposed to acute and chronic environmental stress. Approximate entropy (ApEn) approach is applied in order to investigate the pulse interval (PI) response to two different types of environmental stress: shaker and restrain stress. The performance of ApEn method was evaluated from the parameter selection point of view. The purpose of the study is to quantify the complexity of response to stress and period of recovery after the stress in order to gain an insight in consequences of chronic stress exposure.

Dynamic cerebral autoregulation assessment using chaotic analysis in diabetic autonomic neuropathy

Cerebral autoregulation (CA) was assessed by chaotic analysis based on mean arterial blood pressure (MABP) and mean cerebral blood flow velocity (MCBFV) in 19 diabetics with autonomic neuropathy (AN) and 11 age-matched normal subjects. MABP in diabetics dropped significantly in response to tilting (91.6 +/- 14.9 vs. 74.1 +/- 13.4 mmHg, P < 0.05). Valsalva ratio of heart rate was reduced in diabetics compared to normal (1.1 +/- 0.1 vs. 1.5 +/- 0.2, P < 0.05). It indicated AN affects the vasomotor tone of peripheral vessels and baroreflex. Nonlinear results showed higher correlation dimension values of MABP and MCBFV in diabetics compared to normal, especially MABP (3.7 +/- 2.3 vs. 2.0 +/- 0.8, P < 0.05). It indicated CA is more complicated in diabetics. The lower Lyapunov exponent and the higher Kolmogorov entropy values in diabetics indicated less predictable behavior and higher chaotic degree. This study suggests impaired autoregulation would be more chaotic and less predictable.

Hidden markov models and mutual information analysis to characterize nonlinear dynamics in heart rate variability

A study of nonlinear dynamics of the heart rate variability (HRV) was performed using hidden Markov models (HMM) and Mutual Information (MI). A methodology based on HMM has been developed in the present work. Cardiac RR series were analyzed in the three frequency bands: HF (0.15-0.45Hz), high frequency band; LF (0.04-0.15Hz), low frequency band; VLF (0.003-0.04Hz), very low frequency band. These series (0, observations) were modeled using HMM. The model &#955;=(A,B,&#8719;) was selected so that P(O/&#955;) was locally maximized. Ergodic topology and N=10 states were also considered for this analysis. Different measures based on HMM were defined and obtained from RR time series of 37 Idiopathic Dilated Crdiomyopathy (IDC) patients and 46 healthy subjects (NRM), during awake and sleep stages. Two groups of IDC patients were considered: 11 high risk (HR) patients, after aborted sudden cardiac death (SCD) or who died during the follow up; 26 low risk (LR) patients, without SCD. Some HMM measures showed high percentages (up to 100%) of well classified subjects in all groups.

Correlation dimension analysis of heart rate variability in patients with dilated cardiomyopathy

A correlation dimension analysis of heart rate variability (HRV) was applied to a group of 55 patients with dilated cardiomyopathy (DCM) and 55 healthy subjects as controls. The 24-h RR time series for each subject was divided into segments of 10,000 beats to determine the correlation dimension (CD) per segment. A study of the influence of the time delay (lag) in the calculation of CD was performed. Good discrimination between both groups (p<0.005) was obtained with lag values of 5 or greater. CD values of DCM patients (8.4+/-1.9) were significantly lower than CD values for controls (9.5+/-1.9). An analysis of CD values of HRV showed that for healthy people, CD night values (10.6+/-1.8) were significant greater than CD day values (9.2+/-1.9), revealing a circadian rhythm. In DCM patients, this circadian rhythm was lost and there were no differences between CD values in day (8.8+/-2.4) and night (8.9+/-2.1).

Progressive left ventricular remodeling in patients with hypertrophic cardiomyopathy and severe left ventricular hypertrophy

OBJECTIVES

The aim of this study was to determine the natural history of patients with hypertrophic cardiomyopathy (HCM) and severe left ventricular hypertrophy (LVH) (i.e., maximal left ventricular wall thickness [MLVWT] >/=30 mm) and whether changes in cardiac morphology influence the course of the disease.

BACKGROUND

Severe LVH is common in young and rare among elderly patients with HCM. This has been explained by a high incidence of sudden death. We hypothesized that this age-related difference might be explained by left ventricular wall thinning.

METHODS

A total of 106 (age 33 +/- 15 years; 71 males) consecutive patients with severe LVH underwent history taking, examination, electrocardiography, echocardiography, cardiopulmonary exercise testing, and Holter analysis. Survival data were collected at subsequent clinic visits or by communication with patients and their general practioners. In order to assess morphologic and functional changes, 71 (67.0%) patients (mean age 31 +/- 15 years; 47 males) followed at our institution underwent serial (>/=1 year) assessment.

RESULTS

Of the 106 patients, the majority (78 [71.6%]) were <40 years of age. During follow-up (92 +/- 50 months [range 1 to 169]), 18 (17.0%) patients died or underwent heart transplantation (13 sudden cardiac deaths, 2 heart failure deaths, 1 heart transplantation, 1 stroke, 1 postoperative death). Five-year survival from sudden death was 90.1% (95% confidence interval [CI] 84.0% to 96.3%), and that from heart failure death or transplantation was 97.7% (95% CI 94.5 to 100). In patients serially evaluated over 85 +/- 51 months, there was an overall reduction in MLVWT of 0.6 mm/year (95% CI 0.31 to 0.81, p = 0.00004). Wall thinning >/=5 mm was observed in 41 patients (57.7%; age 35 +/- 13 years; 28 males). On multivariate analysis, the follow-up duration only predicted wall thinning (0.6 mm/year, 95% CI 0.38 to 0.85, p < 0.00001).

CONCLUSIONS

Left ventricular remodeling is common in patients with severe LVH and contributes to the low prevalence of severe LVH seen in middle age and beyond.