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Appl. Sci. 2018, 8(9), 1531; https://doi.org/10.3390/app8091531

Movement Noise Cancellation in Second Derivative of Photoplethysmography Signals with Wavelet Transform and Diversity Combining

School of Electrical Engineering, University of Ulsan, Ulsan 44610, Korea
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Received: 31 July 2018 / Revised: 24 August 2018 / Accepted: 28 August 2018 / Published: 1 September 2018
(This article belongs to the Special Issue Wearable Wireless Devices)
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Abstract

In this paper, we propose an algorithm to remove movement noise from second derivative of photoplethysmography (SDPPG) signals. SDPPG is widely used in healthcare applications because of its easy and comfortable measurement. However, an SDPPG signal is vulnerable to movement, which degrades the signal. Degradation of SDPPG signal shapes can result in incorrect diagnosis. The proposed algorithm detects movement noise in a measurement signal using wavelet transform, and removes movement noise by selecting the best signal from among multiple signals measured at different locations. Experiment results show that the proposed algorithm outperforms the previous filter-based algorithm, and that movement noise with 30% time duration can be reduced by up to 70.89%. View Full-Text
Keywords: SDPPG; movement noise; wavelet transform; diversity combining SDPPG; movement noise; wavelet transform; diversity combining
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Ban, D.; Shahid, S.M.; Kwon, S. Movement Noise Cancellation in Second Derivative of Photoplethysmography Signals with Wavelet Transform and Diversity Combining. Appl. Sci. 2018, 8, 1531.

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