독립 요소 분석을 통한 Photoplethysmography에서의 동잡음 제거

Abstract

In this paper, we propose the method that separates PPG signal and motion artifact signal from two input signals using new independent component analysis algorithm in time domain. In order to eliminate the large level artifact efficiently, block interleaving. lowpass time filtering and innovation processing technique were applied in ICA preprocessing, and FastICA algorithm were applicable. Experiments are made with the numerical simulation and the real PPG signal including four kinds of motion artifact pattern. Our results show that ICA can effectively detect, separate and remove motion artifact in input signals. Then from the separated signals we restore the original PPG signal and propose a new method which computes SpO2 using ICA mixing matrix.