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In a pulse oximeter, clean artifact-free photoplethysmographic (PPG) signals with clearly separable DC and AC parts are necessary for error-free estimation of arterial oxygen saturation (SpO2). Motion artifacts (MA) introduced in the PPG signals due to the movement of a patient result in a significant error in the readings of pulse oximeters and hence are a common cause of oximeter failure and loss of accuracy. In this paper, we present a comparative analysis of using different wavelets for the case of MA reduction from corrupted PPG signals. PPG signals with frequently encountered artifacts (horizontal, vertical and bending motions of finger) were recorded from the subjects and processed with different wavelets. Simulation results and statistical analysis revealed that the Daubechies wavelet performed well for obtaining clean motion artifact-free PPG signal. Interestingly, the wavelet based method proved to be efficient in reducing MA restoring the respiratory information in tact with the PPG.