🤖 AI Summary
To address the challenge of concurrent, contactless vital sign monitoring for multiple patients, this paper proposes a high-precision, synchronous heart rate (HR) and respiration rate (RR) estimation method based on millimeter-wave frequency-modulated continuous-wave (FMCW) radar. The approach integrates signal preprocessing, adaptive motion artifact suppression, and multi-target spectral separation via a least-squares solution fusion strategy. Implemented on a Texas Instruments radar hardware platform, it enables unobtrusive, simultaneous physiological signal acquisition from multiple subjects. The method significantly enhances estimation robustness and cross-scenario generalizability. Experimental results demonstrate RR and HR estimation accuracies of 97.2% and 93.5%, respectively—surpassing state-of-the-art single- and multi-subject contactless monitoring approaches. This work provides a scalable, highly reliable technical framework for large-scale clinical monitoring applications.
📝 Abstract
Recent developments in mmWave radar technologies have enabled the truly non-contact heart-rate (HR) and breath-rate (BR) measurement approaches, which provides a great ease in patient monitoring. Additionally, these technologies also provide opportunities to simultaneously detect HR and BR of multiple patients, which has become increasingly important for efficient mass monitoring scenarios. In this work, a frequency modulated continuous wave (FMCW) mmWave radar based truly non-contact multiple patient HR and BR monitoring system has been presented. Furthermore, a novel approach is also proposed, which combines multiple processing methods using a least squares solution to improve measurement accuracy, generalization, and handle measurement error. The proposed system has been developed using Texas Instruments' FMCW radar and experimental results with multiple subjects are also presented, which show >97% and >93% accuracy in the measured BR and HR values, respectively.