IEEE Trans Biomed Circuits Syst. 2023 Oct;17(5):1074-1083. doi: 10.1109/TBCAS.2023.3315297. Epub 2023 Nov 21.
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.
本文提出了一种运动伪影（MA）消除技术，用于准确的基于光电容积脉搏波（PPG）的心率（HR）估计。使用两个紧密放置的红色和绿色 LED 测量的两个 PPG 信号来消除 MA。所提出的技术利用了两个 PPG 信号的特征：MA 中的高相关性及其不同的交流/直流比。这些特征允许通过自适应滤波器消除 MA，同时保留交流分量。此外，自适应滤波器使用符号-符号最小均方（SS-LMS）算法，最大限度地减少了硬件资源要求。为了验证该技术，实现了一个原型，并对六名受试者进行了三种运动（行走、跑步和下蹲）的实验。与传统的带通滤波绿色 PPG 相比，所提出的 MA 消除方法显著降低了 HR 估计的平均绝对误差（MAE），从 9.83 bpm 平均降低到 1.48 bpm。
