摘要：

针对使用脉搏信号进行长时间心率监测时存在高功耗和易受运动伪迹影响的问题，提出一种从压缩采样脉搏信号中提取心率的算法。利用Lomb-Scargle周期图法从压缩采样的脉搏信号和未压缩的加速度信号中提取频谱，采用最小二乘谱减法获得差分谱。在此基础上，通过谱峰追踪得到心率估计值。实验结果表明，在25倍压缩率下，与TROIKA算法相比，该算法能够降低功耗，且具有较强的抗干扰性和较好的心率估计性能。

关键词: 压缩采样, 脉搏信号, 运动伪迹, 谱减法, 心率估计

Abstract:

Aiming at the problem of high power consumption and vulnerability to motion artifacts for long-term heart rate monitoring using pulse signals,an algorithm for extracting heart rate from compressed sampled pulse signals is proposed.The Lomb-Scargle spectral analysis method is used to extract the spectrum from the compressed sampled pulse signal and the uncompressed acceleration signal.The least squares spectrum subtraction method is used to obtain the differential spectrum.On this basis,the heart rate estimation is obtained by spectral peak tracking.Experimental results show that compared with TROIKA algorithm,the algorithm can reduce power consumption,has strong anti-interference and better heart rate estimation performance at 25 times compression ratio.

Key words: compressive sample, photoplethysmography, motion artifact, spectrum subtraction, heart rate estimation

中图分类号: 

• TP274