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

• Published in: Proceedings 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
• Language: English
• Published: IEEE 14.04.2024
• Subjects: 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
• ISSN: 2379-190X
• DOI: 10.1109/ICASSP48485.2024.10448323

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.