Finding a Suitable Nonlinear Technique to Distinguish Between HRV Data of Cardiac & Non – Cardiac Diseased Subjects
CH.Renu Madhavi1, A.G.Ananth2
1CH.Renu Madhavi, Instrumentation Technology, Visweswaraiah Technological University, RV College Of Engineering, Bangalore, India.
2A.G.Ananth,Department of Telecommunication Engineerin, Visweswaraiah Technological University, RV College Of Engineering, Bangalore, India.
Manuscript received on August 06, 2013. | Revised Manuscript received on August 28, 2013. | Manuscript published on September 05, 2013. | PP: 208-210 | Volume-3, Issue-4, September 2013. | Retrieval Number: D1830093413/2013©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The objective of this paper is to find a nonlinear technique which has better resolution in distinguishing between healthy, cardiac and Non-cardiac diseased subjects. Heart Rate Variability (HRV) data of healthy, cardiac disease and Non-cardiac diseased subjects are analysed using nonlinear techniques. The nonlinear techniques such as Approximate Entropy (ApEn), Sample Entropy (SampEn), Symbolic Entropy (SymbEn), Spectral Entropy (SE) and Correlation Dimension(CD) are applied to the HRV data and the corresponding nonlinear parameters are estimated and compared. Comparison of the estimated parameters revealed best resolution for SampEn to distinguish between healthy, cardiac and Non-cardiac diseased subjects. Further among the Non-cardiac diseased subjects also, SampEn showed higher resolution to distinguish between them. The lowest values of Nonlinear parameters for Non-cardiac diseased subjects when compared to cardiac diseased subjects indicated higher risk of sudden cardiac death for Non-cardiac diseased subjects when compared to cardiac diseased subjects.
Keywords: Cardiac disease, Non-cardiac disease, nonlinear techniques, Thyroid, Depression.