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Real-Time Non-Contact Millimeter Wave Radar-Based Vital Sign Detection

In this paper, the extraction of the life activity spectrum based on the millimeter (mm) wave radar is designed to realize the detection of target objects and the threshold trigger module. The maximum likelihood estimation method is selected to complete the design of the average early warning probab...

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Autores principales: Gao, Zhiqiang, Ali, Luqman, Wang, Cong, Liu, Ruizhi, Wang, Chunwei, Qian, Cheng, Sung, Hokun, Meng, Fanyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9573470/
https://www.ncbi.nlm.nih.gov/pubmed/36236659
http://dx.doi.org/10.3390/s22197560
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author Gao, Zhiqiang
Ali, Luqman
Wang, Cong
Liu, Ruizhi
Wang, Chunwei
Qian, Cheng
Sung, Hokun
Meng, Fanyi
author_facet Gao, Zhiqiang
Ali, Luqman
Wang, Cong
Liu, Ruizhi
Wang, Chunwei
Qian, Cheng
Sung, Hokun
Meng, Fanyi
author_sort Gao, Zhiqiang
collection PubMed
description In this paper, the extraction of the life activity spectrum based on the millimeter (mm) wave radar is designed to realize the detection of target objects and the threshold trigger module. The maximum likelihood estimation method is selected to complete the design of the average early warning probability trigger function. The threshold trigger module is designed for the echo signal of static objects in the echo signal. It will interfere with the extraction of Doppler frequency shift results. The moving target detection method is selected, and the filter is designed. The static clutter interference is filtered without affecting the phase difference between the detection sequences, and the highlight target signal is improved. The frequency and displacement of thoracic movement are used as the detection data. Through the Fourier transform calculation of the sequence, the spectrum value is extracted within the estimated range of the heartbeat and respiration spectrum, and the heartbeat and respiration signals are picked up. The proposed design uses Modelsim and Quartus for CO-simulation to complete the simulation verification of the function, extract the number of logical units occupied by computing resources, and verify the algorithm with the vital signs experiment. The heartbeat and respiration were detected using the sports bracelet; the relative errors of heartbeat detection were 0–6.3%, the respiration detection was 0–9.5%, and the relative errors of heartbeat detection were overwhelmingly less than 5%.
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spelling pubmed-95734702022-10-17 Real-Time Non-Contact Millimeter Wave Radar-Based Vital Sign Detection Gao, Zhiqiang Ali, Luqman Wang, Cong Liu, Ruizhi Wang, Chunwei Qian, Cheng Sung, Hokun Meng, Fanyi Sensors (Basel) Article In this paper, the extraction of the life activity spectrum based on the millimeter (mm) wave radar is designed to realize the detection of target objects and the threshold trigger module. The maximum likelihood estimation method is selected to complete the design of the average early warning probability trigger function. The threshold trigger module is designed for the echo signal of static objects in the echo signal. It will interfere with the extraction of Doppler frequency shift results. The moving target detection method is selected, and the filter is designed. The static clutter interference is filtered without affecting the phase difference between the detection sequences, and the highlight target signal is improved. The frequency and displacement of thoracic movement are used as the detection data. Through the Fourier transform calculation of the sequence, the spectrum value is extracted within the estimated range of the heartbeat and respiration spectrum, and the heartbeat and respiration signals are picked up. The proposed design uses Modelsim and Quartus for CO-simulation to complete the simulation verification of the function, extract the number of logical units occupied by computing resources, and verify the algorithm with the vital signs experiment. The heartbeat and respiration were detected using the sports bracelet; the relative errors of heartbeat detection were 0–6.3%, the respiration detection was 0–9.5%, and the relative errors of heartbeat detection were overwhelmingly less than 5%. MDPI 2022-10-06 /pmc/articles/PMC9573470/ /pubmed/36236659 http://dx.doi.org/10.3390/s22197560 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Gao, Zhiqiang
Ali, Luqman
Wang, Cong
Liu, Ruizhi
Wang, Chunwei
Qian, Cheng
Sung, Hokun
Meng, Fanyi
Real-Time Non-Contact Millimeter Wave Radar-Based Vital Sign Detection
title Real-Time Non-Contact Millimeter Wave Radar-Based Vital Sign Detection
title_full Real-Time Non-Contact Millimeter Wave Radar-Based Vital Sign Detection
title_fullStr Real-Time Non-Contact Millimeter Wave Radar-Based Vital Sign Detection
title_full_unstemmed Real-Time Non-Contact Millimeter Wave Radar-Based Vital Sign Detection
title_short Real-Time Non-Contact Millimeter Wave Radar-Based Vital Sign Detection
title_sort real-time non-contact millimeter wave radar-based vital sign detection
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9573470/
https://www.ncbi.nlm.nih.gov/pubmed/36236659
http://dx.doi.org/10.3390/s22197560
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