摘要
针对运动过程的光电容积脉搏波(photoplethysmography, PPG)信号易受到运动伪影的干扰,使得心率测量困难的问题,提出了一种基于修正加速度的对数归一化变步长自适应滤波(log-normalized least mean square, Log-NLMS)算法。该算法利用角速度对加速度进行卡尔曼滤波修正,去除重力分量。然后将修正后的加速度作为对数归一变步长自适应滤波的参考信号,滤除PPG信号中的运动伪影,最后利用谱峰追踪估计心率。结果表明:该算法估计心率的平均绝对误差较传统算法平均降低了1.4次/min,平均相对误差降低了1.55%,可见本文算法能够有效地去除运动伪影的干扰,获得更为准确的心率。
The photoplethysmography(PPG) signal for exercise is susceptible to interference from motion artifacts, which makes heart rate measurement difficult. A logarithmic normalized variable step adaptive filter algorithm based on corrected acceleration was proposed. The angular velocity was used by the algorithm to perform Kalman filter correction on the acceleration, which removed the gravity component. The corrected acceleration was used as the reference signal of logarithmic normalization variable step size adaptive filtering algorithm to eliminate the motion artifacts in the PPG signal. Finally the heart rate was estimated by spectral peak tracking. The results show that the average absolute error of the estimated heart rate by this algorithm is reduced by 1.4 BPM on average compared with that by the traditional algorithms, and the average relative error is reduced by 1.55%. It can be seen that the proposed algorithm can effectively remove the interference of motion artifacts and obtain a more accurate heart rate.
作者
谭拥
余成波
张林
TAN Yong;YU Cheng-bo;ZHANG Lin(College of Electrical and Electronic Engineering,Chongqing University of Technology,Chongqing 401320,China)
出处
《科学技术与工程》
北大核心
2021年第10期4092-4097,共6页
Science Technology and Engineering
基金
国家自然科学基金(61976030)
斯沃德股份有限公司资助项目(2018Q131)。
