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Distribution Entropy (DistEn) : a complexity measure to detect arrhythmia from short length RR interval time series

Karmakar, Chandan, Udhayakumar, Radhagayathri K. and Palaniswami, Marimuthu 2015, Distribution Entropy (DistEn) : a complexity measure to detect arrhythmia from short length RR interval time series, in EMBC 2015 : Proceedings of the IEEE Engineering in Medicine and Biology Society Annual International Conference, IEEE, Piscataway, N.J., pp. 5207-5210, doi: 10.1109/EMBC.2015.7319565.

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Title Distribution Entropy (DistEn) : a complexity measure to detect arrhythmia from short length RR interval time series
Author(s) Karmakar, ChandanORCID iD for Karmakar, Chandan orcid.org/0000-0003-1814-0856
Udhayakumar, Radhagayathri K.
Palaniswami, Marimuthu
Conference name Engineering in Medicine and Biology Society. Conference (37th : 2015 : Milan, Italy)
Conference location Milan, Italy
Conference dates 25-29 Aug. 2015
Title of proceedings EMBC 2015 : Proceedings of the IEEE Engineering in Medicine and Biology Society Annual International Conference
Publication date 2015
Start page 5207
End page 5210
Total pages 4
Publisher IEEE
Place of publication Piscataway, N.J.
Summary Heart 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.
ISSN 1557-170X
Language eng
DOI 10.1109/EMBC.2015.7319565
Field of Research 090304 Medical Devices
090609 Signal Processing
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2015, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30081605

Document type: Conference Paper
Collection: Centre for Pattern Recognition and Data Analytics
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