Arteriosclerosis feature extraction for human pulse signals

Pulse signal is one of the most important physiological signals in human bodies. It can provide the most important information for disease diagnosis. In this paper, we focus on the human pulse feature extraction based on Empirical Mode Decomposition (EMD). Arteriosclerosis pulse feature extraction based on EMD is studied. We analyze the atherosclerosis pulses by using their modal energy ratio. Simulation results show that the proposed method can be used to distinguish healthy pulses with arteriosclerosis pulses.