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....

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Vydáno v:2025 5th International Conference on Consumer Electronics and Computer Engineering (ICCECE) s. 379 - 383
Hlavní autoři: Xu, Zeping, Xiao, Yan, Wang, Yunpeng, Li, Ji, Song, Kailun, Zhang, Weixin
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 28.02.2025
Témata:
Accuracy
FMCW radar
Fuzzy logic
fuzzy logic inference
Inference algorithms
Interference
Monitoring
Non-contact vital sign monitoring
Radar applications
Real-time systems
Robustness
Sensitivity
Signal to noise ratio
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Shrnutí: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.
DOI:10.1109/ICCECE65250.2025.10985527