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Distribution Entropy (DistEn) : a complexity measure to detect arrhythmia from short length RR interval time series
conference contribution
posted on 2015-01-01, 00:00 authored by Chandan KarmakarChandan Karmakar, Radhagayathri Krishnavilas Udhayakumar, M PalaniswamiHeart rate complexity analysis is a powerful non-invasive means to diagnose several cardiac ailments. Non-linear tools of complexity measurement are indispensable in order to bring out the complete non-linear behavior of Physiological signals. The most popularly used non-linear tools to measure signal complexity are the entropy measures like Approximate entropy (ApEn) and Sample entropy (SampEn). But, these methods become unreliable and inaccurate at times, in particular, for short length data. Recently, a novel method of complexity measurement called Distribution Entropy (DistEn) was introduced, which showed reliable performance to capture complexity of both short term synthetic and short term physiologic data. This study aims to i) examine the competence of DistEn in discriminating Arrhythmia from Normal sinus rhythm (NSR) subjects, using RR interval time series data; ii) explore the level of consistency of DistEn with data length N; and iii) compare the performance of DistEn with ApEn and SampEn. Sixty six RR interval time series data belonging to two groups of cardiac conditions namely `Arrhythmia' and `NSR' have been used for the analysis. The data length N was varied from 50 to 1000 beats with embedding dimension m = 2 for all entropy measurements. Maximum ROC area obtained using ApEn, SampEn and DistEn were 0.83, 0.86 and 0.94 for data length 1000, 1000 and 500 beats respectively. The results show that DistEn undoubtedly exhibits a consistently high performance as a classification feature in comparison with ApEn and SampEn. Therefore, DistEn shows a promising behavior as bio marker for detecting Arrhythmia from short length RR interval data.
History
Event
Engineering in Medicine and Biology Society. Conference (37th : 2015 : Milan, Italy)Pagination
5207 - 5210Publisher
IEEELocation
Milan, ItalyPlace of publication
Piscataway, N.J.Publisher DOI
Start date
2015-08-25End date
2015-08-29ISSN
1557-170XLanguage
engPublication classification
E Conference publication; E1 Full written paper - refereedCopyright notice
2015, IEEETitle of proceedings
EMBC 2015 : Proceedings of the IEEE Engineering in Medicine and Biology Society Annual International ConferenceUsage metrics
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