Abstract
In order to improve the accuracy of heart rate extracted from wearable photoplethysmography (PPG) signal, a new processing method based on moving average filtering is proposed. There are two cascaded moving average filters. The first filter is designed to remove baseline wandering as preprocessing. The second filter whose window size is adjusted according to the additional accelerometer signal is used to remove motion artifacts. During continuous monitoring, the parameters of these two filters change adaptively in accordance with a batch processing method. The results show that the proposed method can reconstruct a better waveform and improve the signal quality for calculating the beats per minute (BPM). Referenced with the vital sign monitoring instrument VS800 of Mindray company, the detecting accuracy of the proposed method is 7%–10% higher than adaptive filtering.
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© 2017 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Chen, Y., Li, D., Li, Y., Ma, X., Wei, J. (2017). Use Moving Average Filter to Reduce Noises in Wearable PPG During Continuous Monitoring. In: Giokas, K., Bokor, L., Hopfgartner, F. (eds) eHealth 360°. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 181. Springer, Cham. https://doi.org/10.1007/978-3-319-49655-9_26
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DOI: https://doi.org/10.1007/978-3-319-49655-9_26
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