skip to main content
Language:
Search Limited to: Search Limited to: Resource type Show Results with: Show Results with: Search type Index

Cardiac arrhythmia detection using cross‐sample entropy measure based on short and long RR interval series

Journal of arrhythmia, 2023-06, Vol.39 (3), p.412-421 [Peer Reviewed Journal]

2023 The Authors. published by John Wiley & Sons Australia, Ltd on behalf of Japanese Heart Rhythm Society. ;2023 The Authors. Journal of Arrhythmia published by John Wiley & Sons Australia, Ltd on behalf of Japanese Heart Rhythm Society. ;2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 1880-4276 ;EISSN: 1883-2148 ;DOI: 10.1002/joa3.12839 ;PMID: 37324769

Full text available

Citations Cited by
  • Title:
    Cardiac arrhythmia detection using cross‐sample entropy measure based on short and long RR interval series
  • Author: Sharma, Kanchan ; Sunkaria, Ramesh Kumar
  • Subjects: Algorithms ; Cardiac arrhythmia ; cardiac arrhythmia detection ; cross sample entropy ; Electrocardiography ; Entropy ; Heart ; irregularity ; Measurement techniques ; Original ; Physiology ; R‐R interval series ; sample entropy ; Time series
  • Is Part Of: Journal of arrhythmia, 2023-06, Vol.39 (3), p.412-421
  • Description: 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 p < .0001. The proposed algorithm is also verified by simulated data. 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, M = 2 and threshold, r = .2. Also, CrossSampEn has been found more consistent than Sample entropy algorithm. The first step of the research work is to extract RR intervals are extracted from ECG signals and utilize pre‐processing techniques to banish outliers from data. The outlier‐free data is utilized to evaluate entropy. In the research work, linear interpolation is utilized to remove outliers. Entropy values indicate the detection of arrhythmia subjects.
  • Publisher: Japan: John Wiley & Sons, Inc
  • Language: English
  • Identifier: ISSN: 1880-4276
    EISSN: 1883-2148
    DOI: 10.1002/joa3.12839
    PMID: 37324769
  • Source: Wiley Open Access Journals
    Journals@Ovid Open Access Journal Collection Rolling
    PubMed Central
    ProQuest Central
    DOAJ Directory of Open Access Journals
Back to results list
INSPIRE LIBRARY - TON DUC THANG UNIVERSITY (84-028) 37 755 057 Feedback
19 Nguyen Huu Tho St. Dist.7, HCM thuvien@tdtu.edu.vn

Copyright © 2017 INSPIRE LIBRARY - TON DUC THANG UNIVERSITY

Searching Remote Databases, Please Wait