ArticleJournal of arrhythmia2023
Cardiac arrhythmia detection using cross-sample entropy measure based on short and long RR interval series.
Article in Journal of arrhythmia, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Generalized Gaussian Distribution Improved Permutation Entropy: A New Measure for Complex Time Series Analysis.Entropy (Basel, Switzerland) · 2024Article
- Slope Entropy Characterisation: An Asymmetric Approach to Threshold Parameters Role Analysis.Entropy (Basel, Switzerland) · 2024Article
- Cardiac arrhythmia detection using cross-sample entropy measure based on short and long RR interval series.Journal of arrhythmia · 2023Article
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Accurate arrhythmia (atrial fibrillation (AF) and congestive heart failure (CHF)) detection is still a challenge in the biomedical signal-processing field. Different linear and nonlinear measures of the electrocardiogram (ECG) signal analysis are used to fix this problem. Methods: Sample entropy (SampEn) is used as a nonlinear measure based on single series to detect healthy and arrhythmia subjects. To follow this measure, the proposed work presents a nonlinear technique, namely, the cross-sample entropy (CrossSampEn) based on two series to quantify healthy and arrhythmia subjects. Results: The research work consists of 10 records of normal sinus rhythm, 20 records of Fantasia (old group), 10 records of AF, and 10 records of CHF. The method of CrossSampEn has been proposed to obtain the irregularity between two same and different R-R (R peak to peak) interval series of different data lengths. Unlike the SampEn technique, the CrossSampEn technique never awards a 'not defined' value for very short data lengths and was found to be more consistent than SampEn. One-way ANOVA test has validated the proposed algorithm by providing a large F value and Conclusions: It is concluded that different RR interval series of approximate 1500 data points and same RR interval series of approximate 1000 data points are required for health-status detection with embedded dimensions,
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