E2MD for reduction of motion artifacts from photoplethysmographic signals

Most of the intensive care units (ICU) are equipped with commercial pulse oximeters for monitoring arterial blood oxygen saturation (SpO₂) and pulse rate (PR). Photoplethysmographic (PPG) data recorded from pulse oximeters usually corrupted by motion artifacts (MA), resulting in unreliable and inaccurate estimated measures of SpO₂. In this paper, a simple and efficient MA reduction method based on Ensemble Empirical Mode Decomposition (E²MD) is proposed for the estimation of SpO₂ from processed PPGs. Performance analysis of the proposed E²MD is evaluated by computing the statistical and quality measures indicating the signal reconstruction like SNR and NRMSE. Intentionally created MAs (Horizontal MA, Vertical MA and Bending MA) in the recorded PPGs are effectively reduced by the proposed one and proved to be the best suitable method for reliable and accurate SpO₂ estimation from the processed PPGs.