Multiscale entropy profiling to estimate complexity of heart rate dynamics

Udhayakumar, Radhagayathri K., Karmakar, Chandan and Palaniswami, Marimuthu 2019, Multiscale entropy profiling to estimate complexity of heart rate dynamics, Physical review E - statistical, nonlinear, and soft matter physics, vol. 100, doi: 10.1103/physreve.100.012405.

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Title Multiscale entropy profiling to estimate complexity of heart rate dynamics
Author(s) Udhayakumar, Radhagayathri K.
Karmakar, ChandanORCID iD for Karmakar, Chandan orcid.org/0000-0003-1814-0856
Palaniswami, Marimuthu
Journal name Physical review E - statistical, nonlinear, and soft matter physics
Volume number 100
Article ID 012405
Total pages 5
Publisher American Physical Society
Place of publication College Park, Md.
Publication date 2019
ISSN 1539-3755
2470-0053
Keyword(s) Science & Technology
Physical Sciences
Physics, Fluids & Plasmas
Physics, Mathematical
Physics
APPROXIMATE ENTROPY
SIGNALS
Summary In the analysis of signal regularity from a physiological system such as the human heart, Approximate entropy (HA) and Sample entropy (HS) have been the most popular statistical tools used so far. While studying heart rate dynamics, it nevertheless becomes more important to extract information about complexities associated with the heart, rather than the regularity of signal patterns produced by it. A complex physiological system does not necessarily produce irregular signals and vice versa. In order to equip a regularity statistic to see through the respective system's level of complexity, the idea of multiscaling was introduced in HS estimation. Multiscaling ideally requires an input signal to be (a) long and (b) stationary. However, the longer the data is the less stationary it is. The requirement multiscaling places on its data length largely limits its accuracy. We propose a novel method of entropy profiling that makes multiscaling require very short signal segments, granting better prospects of signal stationarity and estimation accuracy. With entropy profiling, an efficient multiscale HS based analysis requires only 500-beat signals of atrial fibrillated data, as opposed to the earlier case that required at least 20 000 beats.
Language eng
DOI 10.1103/physreve.100.012405
Indigenous content off
Field of Research 01 Mathematical Sciences
02 Physical Sciences
09 Engineering
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2019, American Physical Society
Persistent URL http://hdl.handle.net/10536/DRO/DU:30128332

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