期刊
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
卷 67, 期 5, 页码 1102-1110出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIM.2017.2770818
关键词
Kalman filtering; motion artifact (MA) removal; photoplethysmography (PPG); signal processing; subspace decomposition
Monitoring of health parameters during physical exercise is an important aspect of both sports and rehabilitation medicine. Photoplethysmography (PPG) is routinely employed for low-cost heart rate (HR) measurement; however, monitoring during physical exercise is made difficult by the presence of motion artifacts. In this paper, we present an approach that combines denoising by subspace decomposition and Fourier-based HR measurement, and finally, smoothing and tracking by a Kalman filter. Using publicly available real-life PPG traces, we demonstrate accuracy and performance by an extensive set of experimental results, comparing them with similar algorithms proposed in the literature.
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