Computation of SpO2 using non-parametric spectral estimation methods from wavelet based motion artifact reduced PPG signals

• Published in: 2011 International Conference on Signal Processing, Communication, Computing and Networking Technologies pp. 776 - 780
• Main Authors: Ram, M. Raghu, Madhav, K. Venu, Krishna, E. Hari, Reddy, K. Nagarjuna, Reddy, K. Ashoka
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.07.2011
• Subjects: Blood; Estimation; Motion artifact; PPG; Signal processing; Spectral Estimation; Time frequency analysis; Wavelet analysis; Wavelet Transform; Wavelet transforms
• ISBN: 1612846548; 9781612846545
• DOI: 10.1109/ICSCCN.2011.6024656

A pulse oximeter measures the arterial blood oxygen saturation (SpO 2 ). The common cause of oximeter failure in computing error- free SpO 2 is motion artifact (MA) corruption in the detected PPG signals. In order to have a low failure rate, the pulse oximeters must be provided with a clean artifact-free PPG signals with clearly separable DC and AC parts from which the SpO 2 is computed in time domain. In this paper, we present non parametric spectral estimation methods for computing SpO 2 . The PPG signals recorded with frequently encountered artifacts (bending, vertical and horizontal motions of finger) were used for validation of the proposed methods. Experimental results revealed that the non-parametric spectral estimation methods are as accurate as the computed values of time domain analysis and the Welch based SpO 2 estimation out performed other non parametric methods. Further, the Daubechies wavelet based method efficiently reduced motion artifacts restoring all the morphological features of the PPG signals.