Signal processing methods for pulse oximetry

Abstract

Current signal processing technology has driven many advances in almost every aspect of life, including medical applications. It follows that applying signal processing techniques to pulse oximetry could also provide major improvements. This research was designed to identify and implement one or more techniques that could improve pulse oximetry oxygen saturation (SpO2) measurements. The hypothesis was that frequency domain analysis could more easily extract the cardiac rate and amplitude of interest from the time domain signal. The focus was on the digital signal processing algorithms that had potential to improve pulse oximetry readings, and then test those algorithms. This was accomplished using the Fast Fourier Transform (FFT) and the Discrete Cosine Transform (DCT). The results indicate that the FFT and DCT computation of oxygen saturation were as accurate without averaging, as weighted moving average (WMA) algorithms currently being used, and directly indicate when erroneous calculations occur.