Research On The Algorithm Of Oxygen Saturation Based On Photoplethysmography

In recent years,as people's life quality continues to improve,health monitoring equipment has been rapidly developed,and people's demand for them also has improved.In the body's physical health indicators,oxygen saturation is an extremely important one.It can reflect the body's oxygen status,and detect a number of cardiovascular parameter and is widely used in clinic and family.However,current oximetry instruments are highly susceptible to motion artifacts,resulting in poor accuracy of heart rate and oximetry detection,especially when the pulse wave signal contains sudden noise,using conventional algorithms to deal with the signal,the result is not satisfactory.Based on the above background,this paper use signal processing algorithms to eliminate noise,proposed based on adaptive noise removal algorithm to remove motion interference;and combine the morphological algorithms and the difference method to detection the pulse wave characteristic parameters to improve the accuracy of the Oxygen saturation calculation.First of all,this paper use the blood oxygen detection equipment for data acquisition,and then analyze the waveform characteristics,on the basis of low-pass smoothing filtering and median filtering to remove the sudden change in the pulse noise and signal in the burr.Improved filtering algorithm for noise removal and initial suppression of motion noise.In order to further eliminate the interference of the motion of blood oxygen detection in dynamic environment,an improved motion interference removal algorithm is designed in this paper to remove motion artifacts by using an adaptive noise cancellation algorithm.Through the noise analysis of pulse wave signal,the envelope signal of PPG is used to extract the AC component and DC component of pulse wave signal.Through the correlation signal is constructed by the characteristic relation of red light and infrared light signal adaptive filtering algorithm to remove motion interference.On the basis of the elimination of motion noise,morphological and differential methods are combined with the physiological characteristics of human pulse wave to extract the characteristic parameters of photoplethysmography and to accurately monitor the maximum and minimum of the signal positioning.Then extraction of peak trough information,and through the oxygen saturation measurement principle to calculate the oxygen saturation.Compared with the existing algorithms,it is proved that the proposed adaptive algorithm for motion interference cancellation and feature parameter extraction can effectively calculate the blood oxygen level in dynamic environment with high accuracy.