Research On Blood Oxygen Saturation Detection And Algorithms Based On Wearable Devices

Photoplethysmography(PPG)is our study of the human circulatory system that contains a lot of physiological and pathological information.Its application areas are developed from the body’s circulation to the respiratory system.The resulf has future prospect in in human blood pressure,blood flow,blood oxygen,brain oxygen,muscle oxygen,blood glucose,pulse rate and respiratory rate.To extract oxygen saturation from PPG signal has become the most important way to measure oxygen saturation.In the intelligent wear,PPG signal detection is used to extract the body’s heart rate signal.On the smart wearable device,there is a lot of noise in the PPG signal,and mainly from the motion artifacts.This paper discusses the issue of removing the artifacts and extracting features from the photorefractive pulse wave signals that collected from the wear equipment to check the saturation of blood oxygen.The technology of non-invasive hemoglobin is discussed.Some optical and physiological knowledge is introduced and my viewpoints are put forward.Based on Lambert-Beer’s law,the mathematic model of blood oxygen saturation is deduced from the mathematical model of transmission oxygen saturation meter.The AFE4403 chip was used for the pulse wave single acquisition device of PPG.Including the two LED lights drive mode and current size control,AFE4403 chip amplification parameter settings,PPG signal acquisition frequency,air occupancy ratio and other issues of research.The acquisition of 135 sets of data was carried out using the acquisition equipment,which provided reliable data for the subsequent PPG signal processing and prediction of oxygen saturation.We studied on PPG signal processing algorithms,including: baseline drift,filter high frequency noise,eliminate motion artifacts and PPG signal feature information extraction.For the baseline drift problem of PPG signal,a zero-phase-shifted IIR infinite impulse response filter is proposed.The PPG signal processing with baseline drift shows that the filter can effectively eliminate the baseline drift of PPG signal.Aiming at the elimination of motion fake noise in PPG signal,an independent component analysis algorithm based on FastICA is proposed to separate the motion artifact signal and PPG signal from the measurement signal.The PPG original signal is used as the noise signal such as PPG signal and motion fake Mixed signal,isolated PPG signal and noise signal.Through the experiment of PPG signal,it is proved that the blind signal processing algorithm can effectively remove the motion artifacts in the PPG signal.The experimental data were collected and the characteristic information was extracted from the PPG signal.The results of the blood oxygen saturation detected by the standard oximeter were used as the reference value,and the experimental results were analyzed by regression analysis to obtain the experience function of the blood oxygen saturation measurement.