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Reseach Article

Heart Variability Analysis by using Non-Linear Techniques and their Comparison

by Harish Kumar, Kamaldeep Kaur, Gurpreet Kaur
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 65 - Number 20
Year of Publication: 2013
Authors: Harish Kumar, Kamaldeep Kaur, Gurpreet Kaur
10.5120/11043-6385

Harish Kumar, Kamaldeep Kaur, Gurpreet Kaur . Heart Variability Analysis by using Non-Linear Techniques and their Comparison. International Journal of Computer Applications. 65, 20 ( March 2013), 33-36. DOI=10.5120/11043-6385

@article{ 10.5120/11043-6385,
author = { Harish Kumar, Kamaldeep Kaur, Gurpreet Kaur },
title = { Heart Variability Analysis by using Non-Linear Techniques and their Comparison },
journal = { International Journal of Computer Applications },
issue_date = { March 2013 },
volume = { 65 },
number = { 20 },
month = { March },
year = { 2013 },
issn = { 0975-8887 },
pages = { 33-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume65/number20/11043-6385/ },
doi = { 10.5120/11043-6385 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:21:07.170530+05:30
%A Harish Kumar
%A Kamaldeep Kaur
%A Gurpreet Kaur
%T Heart Variability Analysis by using Non-Linear Techniques and their Comparison
%J International Journal of Computer Applications
%@ 0975-8887
%V 65
%N 20
%P 33-36
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

An electrocardiogram (ECG) provides information about individual cardiac health. Aside from directly analyzing the ECG signals, researchers and doctors also extract other indirect measurements from the ECG signals and one of the most popular measurements is heart rate variability (HRV). Heart Rate Variability (HRV) measurements analyze how the RR intervals of an ECG signal, which show the variation between consecutive heartbeats, change over time. Heart rate (HR) is a non-stationary signal and its variation may contain indicators of current disease, or warnings about impending cardiac diseases. Hence, HR variation analysis (instantaneous HR against time axis) has become a popular noninvasive tool for assessing the activities of the autonomic nervous system. Computer based analytical tools for in-depth study of data over daylong intervals can be very useful in diagnostics [2]. Therefore, in this paper two non linear techniques Poincare and Recurrence Quantification Analysis are implemented by using Matlab for HRV analysis. Three parameters SD1, SD2 and % REC are taken into consideration for doing the comparison between both the techniques.

References
  1. Task Force of The European Society of cardiology and The North American society of pacing and electrophysiology. Heart rate variability: standards of measurements, physiological interpretation and clinical use. European Heart Journal 1996; 17: 354-381.
  2. U. Rajendra Acharya, K. Paul Joseph, N. Kannathal, Choo Min Lim, Jasjit S. Suri. Heart rate variability: a review. Med Bio Eng Comput (2006) 44:1031–1051.
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  7. Claudia Lerma, Oscar Infante, Hector Perez-Grovas and Marco V. Jose. Poincare plot indexes of heart rate variability capture dynamic adaptations after haemodialysis in chronic renal failure patients. Clinical Physiology & Functional Imaging (2003) 23, pp72–80.
  8. T. Aparicio, E. Pozo and D. Saura. Detecting Determinism Using Recurrence Quantification Analysis: Three Test Procedures. DTECONZ 2005-03.
Index Terms

Computer Science
Information Sciences

Keywords

ECG HRV Poincare Recurrence RQA SD1 SD2 % REC