Abstract
For solving the problem that PPG signals were usually corrupted by motion artifact, a comprehensive approach for heart rate monitoring of real-time wearable devices was proposed in this paper. This method was based on the adaptive noise cancellation technique. Firstly, PPG signals and acceleration signals were pre processed through a band-pass filter. Acceleration signals and red PPG signals would be regarded as a set of noise reference signal. Next, an adaptive filtering algorithm was used to remove the motion artifacts. Finally, the heart rate could be extracted from the denoising PPG signals by using peak to peak value estimation method. The simulation results show that, compared with traditional LMS algorithm and FFT algorithm, the proposed method is more accurate, less error. And the method has the advantages of real-time, high efficiency and simplicity to monitor heart rate in different motion states.
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Acknowledgements
The work was supported by the science research plan of Education Department of Hunan Province: Sparse method for remote sensing image processing.
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Wei, W., Ying, X., Xin, W. (2018). The Heart Rate Monitoring Based On Adaptive Cancellation Method. In: Qiao, F., Patnaik, S., Wang, J. (eds) Recent Developments in Mechatronics and Intelligent Robotics. ICMIR 2017. Advances in Intelligent Systems and Computing, vol 690. Springer, Cham. https://doi.org/10.1007/978-3-319-65978-7_9
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DOI: https://doi.org/10.1007/978-3-319-65978-7_9
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