Vital Signs Measurement Based on High-Frequency Linear Frequency-Modulated Continuous Wave

Authors

Tianrun Wang, University of Beijing Information Science & Technology Beijing Key Laboratory of High Dynamic Navigation Technology, Beijing 100101, China;
Su Zhong, University of Beijing Information Science & Technology Beijing Key Laboratory of High Dynamic Navigation Technology, Beijing 100101, China;
Liu Ning, University of Beijing Information Science & Technology Beijing Key Laboratory of High Dynamic Navigation Technology, Beijing 100101, China;

Abstract

Abstract: Aiming at the inherent limitations and inconveniences of the contact and wearable vital signs measurement tools, and low accuracy of the low frequency mmWave, a non-contact vital signs measurement method based on high-frequency frequency-modulated continuous wave (FMCW) is put forward. By mixing the FMCW’s transmitting and receiving waves, the difference frequency signals and its center frequency are obtained. The distance and speed information of the target is derived from the center frequency. By comparing the heart rate test with two hand rings, it is found that the maximum error is 6.7% and the maximum standard deviation is 3.55277. The maximum errors of the static target with different clothing, the moving target with the same clothing and the moving target with different clothing were 4.5%, 7.2% and 7.7%, respectively.

Recommended Citation

Wang, Tianrun; Zhong, Su; and Ning, Liu (2019) "Vital Signs Measurement Based on High-Frequency Linear Frequency-Modulated Continuous Wave," Journal of System Simulation: Vol. 30: Iss. 11, Article 30.
DOI: 10.16182/j.issn1004731x.joss.201811030
Available at: https://dc-china-simulation.researchcommons.org/journal/vol30/iss11/30

First Page

4292

Revised Date

2018-06-20

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201811030

Last Page

4297

CLC

TN957.51

Recommended Citation

Wang Tianrun, Su Zhong, Liu Ning. Vital Signs Measurement Based on High-Frequency Linear Frequency-Modulated Continuous Wave[J]. Journal of System Simulation, 2018, 30(11): 4292-4297.

DOI

10.16182/j.issn1004731x.joss.201811030