Estimation of average heart rate and blood oxygen saturation via photoplethysmography analysis

Red light and infrared light are commonly employed in the acquisition of Photoplethysmography (PPG) signals due to the differential absorption properties of human tissues across various wavelengths. Hemoglobin (Hb) absorbs red light (660nm), which upon passing through the skin, gets absorbed and reflected by the skin. Minute fluctuations in pulse movements modulate the absorption of red light, enabling the estimation of heart rate. Infrared light (940nm), on the other hand, is predominantly transmitted through the skin and other tissues due to its lesser absorption by water and tissues. This property allows infrared light to penetrate deeper into tissues and traverse through the blood. The attenuation of infrared light can be attributed to its absorption by blood in the vessels under skin, which facilitates the estimation of blood oxygen saturation (SpO2). Thus, a single sensor that combines the red and infrared light can provide insights into both heart rate and blood oxygen levels, making it a standard application in medical monitoring and health tracking. In the experiments, fast Fourier transform (FFT) analysis was employed to obtain the hemoglobin SpO2 values. The optimization process focused on several variables: (i) the total collection period; (ii) processing of hexadecimal to decimal conversion and overflow values; (iii) sampling rate of the data; and (iv) the resolution of spectral analysis outputs. The optimization was intended to identify the minimum sampling rate and the minimum number of discrete data points at which the SpO2 accuracy could be secured. The findings revealed that with a sampling rate of 15 Hz and a collection period of 4.3 s, the SpO2 accuracy can be maintained at an acceptable level by 64-point FFT computation.