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The effect of missing RR-interval data on heart rate variability analysis in the frequency domain

Cited 40 time in Web of Science Cited 51 time in Scopus
Authors

Kim, Ko Keun; Kim, Jung Soo; Lim, Yong Gyu; Park, Kwang Suk

Issue Date
2009-10
Publisher
IOP PUBLISHING LTD
Citation
PHYSIOLOGICAL MEASUREMENT; Vol.30 10; 1039-1050
Keywords
heart rate variability (HRV)missing dataubiquitous healthcarefrequency domain
Abstract
In this study, optimal methods for re-sampling and spectral estimation in frequency-domain heart rate variability (HRV) analysis were investigated through a simulation using artificial RR-interval data. Nearest-neighbour, linear, cubic spline and piecewise cubic Hermite interpolation methods were considered for re-sampling and representative non-parametric, parametric, and uneven approaches were used for spectral estimation. Based on this result, the effects of missing RR-interval data on frequency-domain HRV analysis were observed through the simulation of missing data using real RR-interval tachograms. For this simulation, data including the simulated artefact section (0-100 s) were used; these data were selected randomly from the real RR data obtained from the MIT-BIH normal sinus rhythm RR-interval database. In all, 7182 tachograms of 5 min durations were used for this analysis. The analysis for certain missing data durations is performed by 100 Monte Carlo runs. TF, VLF, LF and HF were estimated as the frequency-domain parameters in each run, and the normalized errors between the data with and without the missing data duration for these parameters were calculated. Rules obtained from the results of these simulations were evaluated with real missing RR-interval data derived from a capacitive-coupled ECG during sleep.
ISSN
0967-3334
Language
English
URI
https://hdl.handle.net/10371/77870
DOI
https://doi.org/10.1088/0967-3334/30/10/005
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College of Medicine/School of Medicine (의과대학/대학원)Biomedical Engineering (의공학전공)Journal Papers (저널논문_의공학전공)
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