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 in | Proceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) pp. 8751 - 8755 |
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Main Authors | , , , , , , , |
Format | Conference Proceeding |
Language | English |
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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. |
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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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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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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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