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Analysis of pulse rate variability derived from photoplethysmography with the combination of lagged Poincare plots and spectral characteristics
journal contributionposted on 05.08.2016, 08:08 by Ping Shi, Yisheng Zhu, John Allen, Sijung Hu
A combination of lagged Poincaré plots and spectral characteristics were used to investigate the effect of cigarette smoking on the autonomic nervous system (ANS). Heart rate variability (HRV) was determined from pulse-to-pulse intervals (PPI) of ear photoplethysmography (PPG) waveforms. Spectral power analysis of the pulse rate variability (PRV)was performed to determine lowfrequency (LF) and high frequency (HF) components, and a lagged Poincaré plot was introduced to evaluate the nonlinear characteristics of PRV. The correlations between lagged Poincaré plot and spectral power indices were studied in a group of apparently healthy habitual cigarette smokers and compared to non-smokers. The width (SD1m) and the length (SD2m) of lagged Poincaré plots significantly shrunk in the smokers for all lags (p < 0.05) except SD14 and SD15. The results of this pilot study indicated that habitual smoking is associated with parasympathetic withdrawal and augments sympathetic nerve activity. The results also demonstrated that the combination of lagged Poincaré plots and spectral characteristics could show promise as a method for distinguishing between different cardiovascular disease groups.
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