Abstract

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Author(s):: HUANG Yiping1; CHEN Zhencheng1; LIANG Yongbo2; ZHU Jianming2; 1. School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004, China 2. School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin 541004, China

Keywords:: respiratory rate photoplethysmography empirical mode decomposition feature extraction respiratory

Abstract:: A method of calculating respiratory rate based on photoplethysmography (PPG) is proposed for quickly detecting the human respiratory rate for wearable medical treatment. After that the PPG signals and the respiratory signals of the human body at the same time are selected from MIMIC Database, the PPG signals are processed by empirical mode decomposition algorithm, thereby obtaining a limited number of intrinsic mode functions of the PPG signals, and an appropriate intrinsic mode function is applied to reconstruct the respiratory signals. Finally, respiratory rate is calculated by extracting features from the reconstructed respiratory signal. The results show that the relative coherence coefficient of the respiratory signals obtained by PPG decomposition and the original respiratory signal is above 0.6, and that the reconstructed and original respiratory rates are also very close, with an accuracy rate up to 0.9. Using the PPG signals to calculate respiratory rate is proved to be feasible, which is of great significance to wearable medical treatment and non-invasive medical diagnosis.