An Effective Respiration Signal Processing System Based on improved EEMD Method and PPG

摘要

An effective signal processing system based on improved Ensemble Empirical Mode Decomposition (EEMD) method is proposed for the analysis of extracting respiration from Photoplethysmography (PPG). The proposed improved EEMD method adaptively adds the noise intensity by calculating the average sub-peak amplitude of PPG. Moreover, an attempt is made to increase the efficiency of the computational process by reducing the number of EMD cycles using the S number convergence criterion based on characteristics of PPG. The proposed algorithm is examined by the on-board DSP and derives better results. It is helpful for non-stationary biomedicalsignal processing.