Estimation of the Pulse Rate Variability based on LMD
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    Abstract:

    In order to overcome the influence of noise and sampling frequency in the process of extracting Pulse Rate Variability(PRV) signal in time domain, a new method of PRV estimation is proposed―Local Mean Decomposition(LMD). Firstly, LMD decomposition and Hilbert transform are performed to the original pulse signal, and each Product Function(PF) component, Pulse signal Instantaneous Frequency(PIF) and marginal spectrum of the pulse signal are obtained. Then the Instantaneous Pulse Rate(IPR) signal is obtained according to the PRV signal frequency distribution. By using the method of estimating IPR signal on LMD and extracting PRV signal in time domain, the pulse signals of 10 college students collected in this study are processed at the same time. It is found that the IPR signal can accurately characterize the PRV signal. LMD method is adopted to estimate the PRV signal in the pulse signal of sleep, visual fatigue and motion state, and the results show that the method can be applied to estimate the PRV signal in different pulse signals. The PRV signals of the young and the old in the MIT-BIH database are analyzed on the entropy of the symbol sequence of short pulse rate. The results show that the method can detect the change of the age. This work provides a method for the effective detection and processing of PRV signals.

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陈彦峰.基于局部均值分解的脉率变异性估计[J]. Journal of Terahertz Science and Electronic Information Technology ,2017,15(6):1032~1038

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History
  • Received:May 28,2016
  • Revised:July 17,2016
  • Adopted:
  • Online: January 03,2018
  • Published: