An Adaptive Filter Based Motion Artifact Cancellation Technique Using Multi-Wavelength PPG for Accurate HR Estimation
Pangi Park, Woobean Lee, SeongHwan Cho
Abstract
This article presents a motion artifact (MA) cancellation technique for accurate photoplethysmography (PPG)-based heart rate (HR) estimation. The MA is canceled using two PPG signals, measured with closely placed red and green LEDs. The proposed technique utilizes the characteristics of the two PPG signals: the high correlation in MA and their different AC/DC ratios. These characteristics allow the MA to be canceled by an adaptive filter while preserving the AC components. In addition, the use of the sign-sign least mean square (SS-LMS) algorithm for the adaptive filter minimizes the hardware resource requirements. To validate the technique, a prototype was implemented and experiments were conducted with six subjects performing three types of movements: walking, running, and squatting. The proposed MA cancellation method significantly reduced the mean absolute error (MAE) in HR estimation, from 9.83 bpm to 1.48 bpm on average, compared to the conventional bandpass filtered green PPG.