Pulse signal de-noising based on wavelet transform and coherent averaging method

A new method of pulse signal de-noising based on wavelet transform and coherent averaging method is proposed. Pulse signal is complex and weak, generally submerged by the interference of baseline drift, motion artifact and high frequency noise. Consequently, it's difficult to measure the heart rate by processing only one single-channel pulse signal, especially when the noise frequency and the pulse signal frequency are in the same frequency range. In this paper, multi-channel pulse signal processing based on wavelet transform and coherent averaging is proposed to solve the above problem. First, the detail coefficients and approximation coefficients of each channel signal are obtained by N layer wavelet decomposition, then reconstructing the signal with high layers coefficients as the high frequency noises always exist in low layers coefficients. In this way we can filter out the high frequency interference. Second, the centerline of the upper and lower envelope curve obtained by cubic spline estimation is subtracted from each reconstructed signal so as to eliminate the baseline drift completely. Finally, the heart rate is acquired with the coherent averaging method which results in the noise being offset each other and the pulse signal being enhanced in the frequency range of pulse wave. The pulse signal and three kinds of noise signals simulated with the superposition of different frequency sin signal were analyzed, besides the experiment of six channel pulse signals measured simultaneously based on PhotoPlethysmoGraphy (PPG) were conducted. The simulation and experiment results showed that this method was superior to the traditional single channel.