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Novel multiscale E-metric cross-sample entropy-based cardiac arrhythmia detection and its performance investigation in reference to multiscale cross-sample entropy-based analysis

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Abstract

Cardiac arrhythmia is a common difficulty of human cardiovascular system and can be evaluated using cardiac rate variability. Multiscale Cross Sample Entropy (MCSEn) is used as a reference to quantify cardiac arrhythmia on the basis of complexity for double-interval series at multiple scales. This measure is failed to provide complexity with reduced scale factors for large data lengths. To hypothesize this measure for two series cardiac data by using coarse-grained process, Multiscale E-metric Cross Sample Entropy (MECSEn) has been proposed and is used to measure complexity between arrhythmia subjects, named atrial fibrillation (AF) and congestive heart failure (CHF) and healthy subjects at multiple scales. Besides short series data and undefined value, MECSEn has come up with a very new concept of banishing the use of a large number of scale factors for evaluating the complexity between two different interval series across multiple scales. It makes the proposed algorithm less time consumer. Both measures have found subjects derived from AF behave as white noise and subjects derived from CHF behave as pink noise. The t test validates MCSEn and the proposed algorithm, MECSEn by providing p < 0.00001. Moreover, MCSEn and MECSEn algorithms are compared with multiscale sample entropy algorithm (MSEn) which uses single cardiac series to evaluate complexity of healthy and arrhythmia subjects.

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Data availability

The datasets generated during and/or analyzed during the current study are available in the PhysioNet repository, [https://physionet.org/].

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Acknowledgements

The authors are thankful to Biomedical Signal and Image Processing Group of Dr B R Ambedkar National Institute of Technology, Jalandhar, for their interest in this work and useful comments to draft the final form of this paper. The authors greatly acknowledge the support of SERB-DST, Government of India, sponsored Research Project sanctioned vide File No. EEQ/2018/000925) Dated: March 22, 2019, to carry out this present work. We would like to thank Dr B R Ambedkar National Institute of Technology, Jalandhar, for laboratory facilities and research environment to carry out this work.

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  1. Department of Electronics and Communication Engineering, Dr B R Ambedkar National Institute of Technology, Jalandhar, Punjab, 144011, India

    Kanchan Sharma & Ramesh Kumar Sunkaria

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Sharma, K., Sunkaria, R.K. Novel multiscale E-metric cross-sample entropy-based cardiac arrhythmia detection and its performance investigation in reference to multiscale cross-sample entropy-based analysis. SIViP 17, 2845–2856 (2023). https://doi.org/10.1007/s11760-023-02503-4

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