Harmonic MUSIC Method for mmWave Radar-based Vital Sign Estimation
Chieh-Hsun Hsieh, Tung-Lin Tsai, and Po-Hsuan Tseng
TL;DR
This paper introduces the harmonic MUSIC algorithm to improve the accuracy of vital sign frequency estimation using mmWave radar, achieving low percentile errors in respiration and heartbeat rates.
Contribution
It proposes a novel harmonic MUSIC method specifically designed for mmWave radar vital sign detection, enhancing frequency estimation accuracy over existing techniques.
Findings
Respiration rate errors less than 3 breaths per minute at the 89th percentile.
Heartbeat rate errors less than 5 beats per minute at the 88th percentile.
Effective for different subjects' vital signs in experimental tests.
Abstract
This paper investigates the application of millimeter-wave (mmWave) radar for the estimation of human vital signs. Aiming to obtain more accurate frequency estimation for periodic signals of respiration and heartbeat, we propose the harmonic MUSIC (HMUSIC) algorithm to consider harmonic components for frequency estimation of vital sign signals. In the experiments, we tested different subjects' vital signs. Experimental results demonstrate that the 89-th percentile errors in respiration rate and the 88-th percentile errors in heartbeat rate are less than 3 respirations per minute and 5 beats per minute.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsWireless Body Area Networks · Non-Invasive Vital Sign Monitoring · Biometric Identification and Security