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A pulse oximeter measures the arterial blood oxygen saturation (SpO2). The common cause of oximeter failure in computing error- free SpO2 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 SpO2 is computed in time domain. In this paper, we present non parametric spectral estimation methods for computing SpO2. 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 SpO2 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.