Investigation on Life Sign Detection Approaches Based on Millimeter Wave Radar

Breathing and heart rate monitoring is of vital significance for the elderly in terms of health, safety, and quality of life, and it is indispensable in disease diagnosis, treatment, and rehabilitation. To deal with the detection of weak bio-signals, a variational mode decomposition (VMD) parameter optimization algorithm with envelope entropy as the fitness function of the Crested Porcupine Optimizer (CPO) is put forward. CPO determines the fitness function for VMD's decomposition and penalty factors. Spectral analysis selects specific intrinsic mode components and reconstructs radar echo signals to extract weak life signals after noise elimination. Experiments demonstrate that this method is more precise, quicker, and efficient.

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Published
2024-12-13
DOI
https://doi.org/10.1109/ichih63459.2024.11064757
Primary Topic
Non-Invasive Vital Sign Monitoring
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article
Field-Weighted Citation Impact
0.00

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article

Investigation on Life Sign Detection Approaches Based on Millimeter Wave Radar

Tian Liu, Mei Liu
Non-Invasive Vital Sign Monitoring
article

Investigation on Life Sign Detection Approaches Based on Millimeter Wave Radar

Tian Liu, Mei Liu
article en

Abstract

Breathing and heart rate monitoring is of vital significance for the elderly in terms of health, safety, and quality of life, and it is indispensable in disease diagnosis, treatment, and rehabilitation. To deal with the detection of weak bio-signals, a variational mode decomposition (VMD) parameter optimization algorithm with envelope entropy as the fitness function of the Crested Porcupine Optimizer (CPO) is put forward. CPO determines the fitness function for VMD's decomposition and penalty factors. Spectral analysis selects specific intrinsic mode components and reconstructs radar echo signals to extract weak life signals after noise elimination. Experiments demonstrate that this method is more precise, quicker, and efficient.

Jilin University of Chemical Technology (CN), Guangdong University of Petrochemical Technology (CN)
National Natural Science Foundation of China
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Openalex Percentile: Top 74%
Non-Invasive Vital Sign Monitoring
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