Journal article
Entropy profiling: A reduced—parametric measure of kolmogorov—sinai entropy from short-term hrv signal
C Karmakar, R Udhayakumar, M Palaniswami
Entropy | MDPI | Published : 2020
DOI: 10.3390/e22121396
Abstract
Entropy profiling is a recently introduced approach that reduces parametric dependence in traditional Kolmogorov-Sinai (KS) entropy measurement algorithms. The choice of the threshold parameter r of vector distances in traditional entropy computations is crucial in deciding the accuracy of signal irregularity information retrieved by these methods. In addition to making parametric choices completely data-driven, entropy profiling generates a complete profile of entropy information as against a single entropy estimate (seen in traditional algorithms). The benefits of using “profiling” instead of “estimation” are: (a) precursory methods such as approximate and sample entropy that have had the ..
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Awarded by Australian Research Council
Funding Acknowledgements
This work was supported by the Australian Research Council (ARC) Discovery Project under grant DP190101248.