Heart Variability Analysis by using Non-Linear Techniques and their Comparison
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10.5120/11043-6385 |
Harish Kumar, Kamaldeep Kaur and Gurpreet Kaur. Article: Heart Variability Analysis by using Non-Linear Techniques and their Comparison. International Journal of Computer Applications 65(20):33-36, March 2013. Full text available. BibTeX
@article{key:article,
author = {Harish Kumar and Kamaldeep Kaur and Gurpreet Kaur},
title = {Article: Heart Variability Analysis by using Non-Linear Techniques and their Comparison},
journal = {International Journal of Computer Applications},
year = {2013},
volume = {65},
number = {20},
pages = {33-36},
month = {March},
note = {Full text available}
}
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
- 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.
- 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.
- N Jafarnia Dabanloo, S Parvaneh, AM Nasrabadi . Utilizing Occurrence Sequence of Heart Rate's Phase Space Points in order to Discriminate Heart Arrhythmia. Proceedings of the 17th Iranian Conference of Biomedical Engineering; (ICBME2010), 3-4 November 2010.
- A Heitmann, T Hubner, R Schroeder, S Perz, A Voss . Ability of heart rate variability as a screening tool for heart disease in men. Computers in cardiology 2009; 36: 825 – 828.
- Joseph P. Zbilut, Nitza Thomasson, Charles L. Webber. Recurrence quantification analysis as a tool for nonlinear exploration of nonstationary cardiac signals. J. P. Zbilut et al. / Medical Engineering & Physics 24 (2002) 53–60.
- Norbert Marwan, M. Carmen Romano, Marco Thiel, Jurgen Kurths. Recurrence plots for the analysis of complex systems. N. Marwan et al. / Physics Reports 438 (2007) 237– 329.
- 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.
- T. Aparicio, E. Pozo and D. Saura. Detecting Determinism Using Recurrence Quantification Analysis: Three Test Procedures. DTECONZ 2005-03.