Motion Noise Cancelation in Heartbeat Sensing using Accelerometer and Adaptive Filter

Abstract

This letter focuses on suppressing the motion artifact of wrist photoplethysmographic heart rate signals using an accelerometer based adaptive filter. Monitoring of the heart signal can offer important insights with regard to health and wellness. The objective of the experiment conducted here is to recover the distorted signal resulting from body movement while measuring the heart rate signal noninvasively from the wrist. The class of filters, known as adaptive filters, that can extract meaningful information from the distorted signal, used predetermined initial conditions to equalize the signal distortion due to motion. Adaptive filters of least mean-square (LMS), Kalman filter, and recursive least-squares (RLS) were used in this study to recover the distorted heart rate signal. This study also presented a comparison on utilized filters that can be used for recovering of the heart rate signal.