Fingertip pulse rate variability extraction based on extreme-point symmetric mode decomposition

Abstract

To solve shortcomings of being sensitive to noise and waveform when using threshold method to extract pulse rate variability (PRV) at this stage, a method using extreme-point symmetric mode decomposition to extract PRV signals from pulse waves with noise is proposed. A Butterworth filter is used to remove the baseline drift, the DC mode and power frequency noise, which can effectively avoid noise interference when identifying peak points. The pre-processed data is decomposed by extreme-point symmetric mode decomposition to select the corresponding mode of the main wave, thereby reducing the difficulty of feature point extraction. Compared with the threshold method, the extraction method proposed in this paper is more intuitive and can self-adaptively select the best decomposition layer. This method is suitable for the extraction of fingertip PRV under complex noise and some disease statuses.