Improved Fuzzy Logic Inference Algorithm for Vital Sign Monitoring Using FMCW Radar*

Vital sign monitoring technology based on FMCW radar has become a research hotspot due to its high sensitivity and non-invasive nature. Compared to traditional methods, the fuzzy logic inference methods based on harmonic and intermodulation components proposed in recent years offer higher accuracy. However, these methods are more susceptible to interference from spurious peaks, making them highly sensitive to the configuration of membership functions, which limits the overall performance of the algorithm. To solve this problem, this paper proposes an improved fuzzy logic algorithm based on multi-range bin combination (MRBCIFL). By jointly optimizing the signals from multiple range bins, the proposed algorithm effectively suppresses spurious peak interference and improves the quality of input data for fuzzy logic inference. Experimental results demonstrate that the MGCIFL method significantly improves the accuracy and robustness of heartbeat frequency estimation.

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Publication Details

Published
2025-02-28
DOI
https://doi.org/10.1109/iccece65250.2025.10985527
Primary Topic
Non-Invasive Vital Sign Monitoring
Type
article
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article

Improved Fuzzy Logic Inference Algorithm for Vital Sign Monitoring Using FMCW Radar*

Weixin Zhang, Yunpeng Wang, Xiao Yan, Ji Li et al.
Non-Invasive Vital Sign Monitoring
article

Improved Fuzzy Logic Inference Algorithm for Vital Sign Monitoring Using FMCW Radar*

Weixin Zhang, Yunpeng Wang, Xiao Yan, Ji Li, Zeping Xu, Kailun Song
article en

Abstract

Vital sign monitoring technology based on FMCW radar has become a research hotspot due to its high sensitivity and non-invasive nature. Compared to traditional methods, the fuzzy logic inference methods based on harmonic and intermodulation components proposed in recent years offer higher accuracy. However, these methods are more susceptible to interference from spurious peaks, making them highly sensitive to the configuration of membership functions, which limits the overall performance of the algorithm. To solve this problem, this paper proposes an improved fuzzy logic algorithm based on multi-range bin combination (MRBCIFL). By jointly optimizing the signals from multiple range bins, the proposed algorithm effectively suppresses spurious peak interference and improves the quality of input data for fuzzy logic inference. Experimental results demonstrate that the MGCIFL method significantly improves the accuracy and robustness of heartbeat frequency estimation.

Guilin University, Guilin University of Electronic Technology (CN)
Openalex Percentile: Top 90%
Non-Invasive Vital Sign Monitoring
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