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Motion Artifact Reduction for Wrist-Worn Photoplethysmograph Sensors Based on Different Wavelengths

1
Holst Centre/imec, 5656AE Eindhoven, The Netherlands
2
Department of Electrical Engineering, Eindhoven University of Technology, 5600MB Eindhoven, The Netherlands
3
imec vzw, 3001 Leuven, Belgium
4
Department of Electrical Engineering, KU Leuven, 3001 Leuven, Belgium
*
Authors to whom correspondence should be addressed.
Sensors 2019, 19(3), 673; https://doi.org/10.3390/s19030673
Received: 31 December 2018 / Revised: 3 February 2019 / Accepted: 5 February 2019 / Published: 7 February 2019
(This article belongs to the Special Issue Wearable and Implantable Sensors and Electronics Circuits)
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Abstract

Long-term heart rate (HR) monitoring by wrist-worn photoplethysmograph (PPG) sensors enables the assessment of health conditions during daily life with high user comfort. However, PPG signals are vulnerable to motion artifacts (MAs), which significantly affect the accuracy of estimated physiological parameters such as HR. This paper proposes a novel modular algorithm framework for MA removal based on different wavelengths for wrist-worn PPG sensors. The framework uses a green PPG signal for HR monitoring and an infrared PPG signal as the motion reference. The proposed framework includes four main steps: motion detection, motion removal using continuous wavelet transform, approximate HR estimation and signal reconstruction. The proposed algorithm is evaluated against an electrocardiogram (ECG) in terms of HR error for a dataset of 6 healthy subjects performing 21 types of motion. The proposed MA removal method reduced the average error in HR estimation from 4.3, 3.0 and 3.8 bpm to 0.6, 1.0 and 2.1 bpm in periodic, random, and continuous non-periodic motion situations, respectively. View Full-Text
Keywords: photoplethysmography; motion artifacts; heart rate; continuous wavelet transforms photoplethysmography; motion artifacts; heart rate; continuous wavelet transforms
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Zhang, Y.; Song, S.; Vullings, R.; Biswas, D.; Simões-Capela, N.; van Helleputte, N.; van Hoof, C.; Groenendaal, W. Motion Artifact Reduction for Wrist-Worn Photoplethysmograph Sensors Based on Different Wavelengths. Sensors 2019, 19, 673.

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