Abstract
This paper proposes an algorithm for eliminating motion artifacts in heart rate monitoring using a photoplethysmography (PPG) sensor. No additional hardware, such as accelerometers or other reference signals, is needed. The algorithm improves the quality of PPG signals by implementing a comb filter during signal processing. The proposed slow–fast adaptive comb filter (SFACF) distinguishes motion artifacts in PPG signals based on harmonic and continuous features of the heart rate. The effectiveness of fundamental and harmonic frequency enhancement in real time is experimentally demonstrated, with the heart rate updated every second. The performance of the SFACF, which does not require additional reference signals, is compared with those of adaptive noise cancellation (ANC) and spectral peak search-comb filtering (SPS-CF). It is found that for a low-quality PPG signal, the SFACF outperforms ANC and SPS-CF. Finally, measurements obtained using a commercial heart rate monitor and the proposed algorithm are shown to be highly correlated.
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