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Reseach Article

Optimal ECG Sampling Rate for Non-Linear Heart Rate Variability

Published on August 2015 by Manjit Singh, Butta Singh, Vijay Kumar Banga
International Conference on Advancements in Engineering and Technology
Foundation of Computer Science USA
ICAET2015 - Number 7
August 2015
Authors: Manjit Singh, Butta Singh, Vijay Kumar Banga
25d42adc-2dbf-4d38-ab99-473fcf4323d6

Manjit Singh, Butta Singh, Vijay Kumar Banga . Optimal ECG Sampling Rate for Non-Linear Heart Rate Variability. International Conference on Advancements in Engineering and Technology. ICAET2015, 7 (August 2015), 22-26.

@article{
author = { Manjit Singh, Butta Singh, Vijay Kumar Banga },
title = { Optimal ECG Sampling Rate for Non-Linear Heart Rate Variability },
journal = { International Conference on Advancements in Engineering and Technology },
issue_date = { August 2015 },
volume = { ICAET2015 },
number = { 7 },
month = { August },
year = { 2015 },
issn = 0975-8887,
pages = { 22-26 },
numpages = 5,
url = { /proceedings/icaet2015/number7/22255-4101/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Advancements in Engineering and Technology
%A Manjit Singh
%A Butta Singh
%A Vijay Kumar Banga
%T Optimal ECG Sampling Rate for Non-Linear Heart Rate Variability
%J International Conference on Advancements in Engineering and Technology
%@ 0975-8887
%V ICAET2015
%N 7
%P 22-26
%D 2015
%I International Journal of Computer Applications
Abstract

The principle difficulty with the analysis of the heart rate variability (HRV) is that heart rate dynamics are non-linear and non-stationary. Detrended fluctuation analysis (DFA) and correlation dimension (CD) are non-linear HRV measures to quantify fractal-like autocorrelation properties and to characterize the complex behaviour of nonlinear time series. Optimal ECG sampling rate is an important issue for accurate quantification of HRV. High ECG sampling rate results in very high processing time and low sampling rate produces signal quality degradation results in clinically misinterpreted HRV. In this work the impact of ECG sampling frequency on non-linear HRV have been quantified in terms of short-range & long-range DFA and CD on short-term (N=200), medium-term (N=500) and long-term (N=1000) data. Non-linear HRV parameters are found to be sensitive to ECG sampling frequency and effect of sampling frequency will be a function of data length.

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Index Terms

Computer Science
Information Sciences

Keywords

Ecg Hrv Sampling Frequency Dfa Cd Signal Processing.