The effect of missing RR-interval data on heart rate variability analysis in the frequency domain
作者： Ko Keun Kim , Jung Soo Kim , Yong Gyu Lim , Kwang Suk Park
DOI: 10.1088/0967-3334/30/10/005
关键词:
摘要: 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 piecewise Hermite interpolation considered representative non-parametric, parametric, uneven approaches used estimation. Based on result, the effects of missing data HRV observed real tachograms. For simulation, including simulated artefact section (0–100 s) used; these selected randomly from RR obtained MIT-BIH normal sinus rhythm database. all, 7182 tachograms 5 min durations analysis. The certain is performed by 100 Monte Carlo runs. TF, VLF, LF HF estimated as parameters each run, normalized errors between with without duration calculated. Rules results simulations evaluated derived capacitive-coupled ECG during sleep.
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