Enabling Orientation-Free Mmwave-Based Vital Sign Sensing with Multi-Domain Signal Analysis

Contactless vital signs estimation using mmWave radar has gained significant attention. However, existing studies are built upon the radar being directed facing the thorax to capture fine-grained vital signs, ignoring the angle variation between the radar and thorax in practical deployment. In this...

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Published inProceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) pp. 8751 - 8755
Main Authors Gong, Hanqin, Zhang, Dongheng, Chen, Jinbo, Li, Yadong, Xu, Guixin, Yuan, Yuqin, Hu, Yang, Chen, Yan
Format Conference Proceeding
LanguageEnglish
Published IEEE 14.04.2024
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Abstract Contactless vital signs estimation using mmWave radar has gained significant attention. However, existing studies are built upon the radar being directed facing the thorax to capture fine-grained vital signs, ignoring the angle variation between the radar and thorax in practical deployment. In this paper, we propose a spatial-temporal optimization model to estimate the human body orientations between the radar and thorax through extracting the multi-domain features of reflected signal. By aligning the signal variation captured from different angles, we can realize orientation-free vital sign sensing. The system achieves an average angle estimation error of 13.1°, and a 14.8% discrepancy reduction in terms of the mean absolute error of the signal captured at different angles.
AbstractList Contactless vital signs estimation using mmWave radar has gained significant attention. However, existing studies are built upon the radar being directed facing the thorax to capture fine-grained vital signs, ignoring the angle variation between the radar and thorax in practical deployment. In this paper, we propose a spatial-temporal optimization model to estimate the human body orientations between the radar and thorax through extracting the multi-domain features of reflected signal. By aligning the signal variation captured from different angles, we can realize orientation-free vital sign sensing. The system achieves an average angle estimation error of 13.1°, and a 14.8% discrepancy reduction in terms of the mean absolute error of the signal captured at different angles.
Author Yuan, Yuqin
Li, Yadong
Zhang, Dongheng
Xu, Guixin
Chen, Jinbo
Hu, Yang
Chen, Yan
Gong, Hanqin
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  organization: University of Science and Technology of China,Hefei,China
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Snippet Contactless vital signs estimation using mmWave radar has gained significant attention. However, existing studies are built upon the radar being directed...
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StartPage 8751
SubjectTerms Biological system modeling
body orientation
Estimation error
Feature extraction
millimeter wave radar
Signal processing algorithms
Thorax
vital signs
Wireless communication
Wireless sensing
Wireless sensor networks
Title Enabling Orientation-Free Mmwave-Based Vital Sign Sensing with Multi-Domain Signal Analysis
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