Xie Qingsong, Zhang Qirui, Wang Guoxing, Lian Yong
Annu Int Conf IEEE Eng Med Biol Soc. 2018 Jul;2018:3568-3571. doi: 10.1109/EMBC.2018.8512925.
This study presents a robust heart rate monitoring algorithm using photoplethysmography (PPG) signal during physical exercise. The proposed method combines two stage: motion artifact removal and frequency refinement. The cascaded normalized least mean square adaptive filter is used to attenuate the noise introduced by motion artifacts in the PPG signal. A phase vocoder technique is used to refine the frequency calculated by Fourier Transform, from which the heart rate is finally tracked. On a publicly available database of twelve PPG recordings, the proposed technique obtains an average absolute error (AAE) of 1.08 beat per minute (BPM). Person correlation coefficient of 0.997 is achieved between true heart rate and estimated heart rate. In contrast to other available approaches, the proposed method has merely one parameter to tune in spectral peak tracking step for heart rate estimation.
本研究提出了一种在体育锻炼期间使用光电容积脉搏波描记法（PPG）信号进行稳健心率监测的算法。所提出的方法包括两个阶段：运动伪影去除和频率细化。级联归一化最小均方自适应滤波器用于衰减PPG信号中由运动伪影引入的噪声。一种相位声码器技术用于细化通过傅里叶变换计算出的频率，最终从中跟踪心率。在所公开的包含12个PPG记录的数据库上，所提出的技术获得了每分钟1.08次心跳（BPM）的平均绝对误差（AAE）。真实心率与估计心率之间的皮尔逊相关系数达到了0.997。与其他现有方法相比，所提出的方法在用于心率估计的频谱峰值跟踪步骤中只需调整一个参数。
