EMD-Based Adaptive Wavelet Threshold for Pulse Wave Denoising

Analysis of the Radial Pulse Wave and its Clinical Applications: A Survey

“…Wang et al used a Savitzky-Golay smoothing filter to remove the random noise higher than 15 Hz and enhanced the pulse waveform [31]. Combining with the method of empirical mode decomposition, Xu et al proposed an adaptive wavelet threshold denoising method and showed that when the SNR was low, the denoising performance of this method was better than the traditional wavelet threshold denoising method [32]. Wang et al proposed a method based on adaptive cascade thresholding to remove the disturbance intervals and showed that an adaptive cascade threshold method could be used to obtain a stable pulse wave [33].…”

“…It is difficult to accurately extract the waveform features and describe the morphological changes. To obtain a corruption-free and more stable radial signal, the waveform preprocessing can not only reduce the interference components [28][29][30][31][32][33], but should also analyze the morphology of radial pulse waves over a long period [34][35][36][37][38]. The purpose of feature extraction is to analyze the information represented by radial pulse waves.…”