Exercise Vital Signs Detection Employing FMCW Radar and Artificial Neural Networks

King Leong Li; Shih-Hsuan Lai; Kyle Cheng; Lindor Henrickson; Irwin Chen; Vincent Wu; Jyehong Chen

doi:10.1364/CLEO_AT.2021.JW1A.149

Conference on Lasers and Electro-Optics
OSA Technical Digest (Optica Publishing Group, 2021),
paper JW1A.149
•https://doi.org/10.1364/CLEO_AT.2021.JW1A.149

Exercise Vital Signs Detection Employing FMCW Radar and Artificial Neural Networks

King Leong Li, Shih-Hsuan Lai, Kyle Cheng, Lindor Henrickson, Irwin Chen, Vincent Wu, and Jyehong Chen

CLEO: QELS_Fundamental Science 2021

San Jose, California United States
9–14 May 2021
ISBN: 978-1-943580-91-0

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Joint Poster Session II (JW1A)

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K. L. Li, S. Lai, K. Cheng, L. Henrickson, I. Chen, V. Wu, and J. Chen, "Exercise Vital Signs Detection Employing FMCW Radar and Artificial Neural Networks," in Conference on Lasers and Electro-Optics, J. Kang, S. Tomasulo, I. Ilev, D. Müller, N. Litchinitser, S. Polyakov, V. Podolskiy, J. Nunn, C. Dorrer, T. Fortier, Q. Gan, and C. Saraceno, eds., OSA Technical Digest (Optica Publishing Group, 2021), paper JW1A.149.

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Abstract

We present a frequency modulated continuous wave (FMCW) radar system for non-contact heart rate monitoring during exercise. 90% accuracy predictions are achieved by employing a modified MobileNetV3 model for regression analysis.

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