ISSN 1812-7231 Klin.inform.telemed. Volume 14, Issue 15, 2019, Pages 67-73
A. Martynenko1, G. Raimondi2, N. Budreiko1
1V. N. Karazin Kharkiv National University, School of Medicine, Ukraine
2University of Roma "Sapienza", Italy
Robust entropy estimator for heart rate variability
Introduction. Non-linear methods of analysis have found widespread use in the heart rate variability (HRV) technology, when the long-term HRV records are available. Using one of the effective nonlinear methods of analysis of HRV entropy for the standard 5-min HRV records is suppressed by unsatisfactory accuracy of available methods in case of short records (usually, doctors have 300–600 RRs during standard 5-min HRV record), as well as complexity and ambiguity of choosing additional parameters for known methods of calculating entropy ApEn, SampEn, MSE and etc.
The purpose of the work. Building a robust formula for calculating entropy (EnRE) with high accuracy for limited series of RR-intervals observed in a standard 5-minute HRV record, i. e. with N≈300–600. As well as demonstrating the capabilities of the EnRE formula on a series of statistical distributions and in diagnosing the congestive heart failure.
Materials and Methods. We used MIT-BIH long-term HRV records for Normal Sinus Rhythm (NSR) and Congestive Heart Failure (CHF). In order to analyze the accuracy of EnRE, we used the known statistical distributions (Normal, Uniform, Exponential, Lognormal, Pareto) with their precise entropy values.
The results of the study. We have shown the effectiveness of the developed EnRE formula for time series of limited length (N = 300–600) using the example of various types of statistical distributions that simulate human HRV ranges, and also demonstrated high accuracy of classification of cases of NSR and CHF for standard 5 min segments from MIT-BIH database of HRV records, using EnRE and EnRE(sort).
Conclusion. Proposed in the article is generalized form for Robust Entropy Estimator, which allows, for time series of limited length (N= 300–600), to calculate entropy value that differs from a precise one by 0,5–2,9%, as demonstrated for various random distributions. On standard 5-min segments from MIT-BIH database of HRV records, we have shown the usage of EnRE and EnRE (sort) for classification of cases of Normal Sinus Rhythm and Congestive Heart Failure with indicators of quality of division into groups: Se = 0,76, Sp = 0,98, Acc = 0,90.
Hearth rate variability, Entropy, Congestive heart failure
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