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
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.