Radar-Beat: Contactless beat-by-beat heart rate monitoring for life scenes

Background and objective: Heartbeat is a crucial vital sign, and radio-frequency technology can measure the micro-vibration of the body surface from a distance and extract the heartbeat signal, which can solve the compliance problem caused by wearable sensors. However, most existing works verify short-term controlled experiments and seldom consider the challenges posed by random body movements and posture changes during long-term monitoring in daily life scenarios. In this article, we propose a systematic solution called Radar-Beat, which enables accurate heartbeat monitoring using an mmWave FMCW radar device. Our goal is to promote the integration of contactless heartbeat monitoring into life scenarios. Methods: We proposes a sensitive body motion detection algorithm and an optimal Range-bin selection algorithm, which can automatically identify body motion and update the best heartbeat signal channel. Then, we construct a personalized heartbeat template for each signal segment and propose a global optimization model to improve the accuracy of heartbeat length estimation. Results: We use the synchronized ECG signal as the ground truth, results show strong agreement between Radar-Beat and synchrony ECG devices for heart rate and inter-beat interval (IBI) measurements in healthy subjects. In the heartbeat monitoring experiment for a total of 72 h and 56 min involving 11 participants, under a time coverage of 91.2%, the median error of IBI estimation was 12 ms. Conclusion: Radar-Beat has strong robustness to different individuals in different postures and positions. It can be deployed in a hospital bed or home to enable continuous heartbeat monitoring in an unobtrusive way.

Automated summary

This article proposes a systematic solution called Radar-Beat, which uses mmWave FMCW radar device to accurately monitor heartbeats. It addresses the compliance problem caused by wearable sensors. By using sensitive body motion detection algorithm and optimal range-bin selection algorithm, it can automatically identify body motion and update the heartbeat signal channel, as well as construct personalized heartbeat templates and a global optimization model to improve the accuracy of heartbeat length estimation. The results demonstrate strong agreement between Radar-Beat and synchronized ECG devices in heart rate and inter-beat interval measurements for healthy subjects.