An Implementation of Motion Artifacts Elimination for PPG Signal Processing Based on Recursive Least Squares Adaptive Filter

In Photoplethysmographic (PPG) signals analysis, the accuracy and stability are highly affected by Motion Artifacts (MAs) disturbances. In this paper, we adopt an adaptive and efficient approach based on the developed DC Remover method and Recursive Least Squares (RLS) adaptive filter for reducing MAs from PPG signals in real time. The experimental results of this work show a high correlation coefficient between Electrocardiography (ECG)-derived heart rate and PPG-derived heart rate, which is higher than 0.8504 of the R value, a high agreement by Bland-Altman analysis in the limits of agreement represent the 95% confidence interval and the standard deviation is 3.81 BPM (Beats Per Minutes). An overall PPG signal with higher signal quality is obtained. Further, the precision of heart rate calculated by PPG is improved.