A Wearable Photoplethysmographic System Realization with Efficient Motion Artifact Reduction Method Based on Recursive Least Squares Adaptive Filtering Algorithm

Abstract

The appearances of Motion Artifacts (MAs) in the photoplethysmographic (PPG) signals is one of the major obstacles to improve the accuracy and the stability of the signals analysis. In this paper, we present an effective and adaptive method based on DC Remover method and Recursive Least Squares (RLS) adaptive filter for reducing MAs disturbances from PPG signals. The results achieved by the presented methodology show a high correlation coefficient between Electrocardiography derived heart rate and PPG-derived heart rate (R=0.8054), moreover, the accuracy of heart rate monitoring was improved. The proposed system was implemented in hardware design for wearable and home-care applications.