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.
Paper
Full text
Enabling Orientation-Free Mmwave-Based Vital Sign Sensing with Multi-Domain Signal Analysis
Semantic Scholar · Engineering · 2024
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.