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 |
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IEEE
28.02.2025
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| 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. |
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| AbstractList | 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. |
| Author | Xiao, Yan Song, Kailun Wang, Yunpeng Li, Ji Xu, Zeping Zhang, Weixin |
| Author_xml | – sequence: 1 givenname: Zeping surname: Xu fullname: Xu, Zeping email: 852040446@qq.com organization: School of Computer and Network Security, Guilin University of Electronic Science and Technology,Guilin,China – sequence: 2 givenname: Yan surname: Xiao fullname: Xiao, Yan email: yan.xiao@locaris.cn organization: Henan Locaris Intelligent Technology Research Institute, Zhengzhou Locaris Technology co.ltd,Zhengzhou,China – sequence: 3 givenname: Yunpeng surname: Wang fullname: Wang, Yunpeng email: 2424142776@qq.com organization: School of Computer and Network Security, Guilin University of Electronic Science and Technology,Guilin,China – sequence: 4 givenname: Ji surname: Li fullname: Li, Ji email: Liji@guet.edu.cn organization: School of Computer and Network Security, Guilin University of Electronic Science and Technology,Guilin,China – sequence: 5 givenname: Kailun surname: Song fullname: Song, Kailun email: 1783258793@qq.com organization: School of Computer and Network Security, Guilin University of Electronic Science and Technology,Guilin,China – sequence: 6 givenname: Weixin surname: Zhang fullname: Zhang, Weixin email: 1547313967@qq.com organization: School of Computer and Network Security, Guilin University of Electronic Science and Technology,Guilin,China |
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| Snippet | 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... |
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| StartPage | 379 |
| SubjectTerms | 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 |
| Title | Improved Fuzzy Logic Inference Algorithm for Vital Sign Monitoring Using FMCW Radar |
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