FMCW-based contactless heart rate monitoring

• Published in: Scientific reports Vol. 15; no. 1; pp. 2616 - 20
• Main Authors: Hao, Zhanjun, Gao, Yifei, Tang, Yangyang, Wang, Yue, Fan, Kai, Li, Fenfang
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 21.01.2025; Nature Publishing Group; Nature Portfolio
• Subjects: 639/166/987; 639/705/117; Adult; Algorithms; Bandpass filtering; Cardiovascular diseases; Female; Frequency dependence; Global health; Heart diseases; Heart rate; Heart Rate - physiology; Heartbeat signals; Humanities and Social Sciences; Humans; Male; Millimeter wave; Monitoring; Monitoring, Physiologic - methods; multidisciplinary; Public health; Radar; Respiration; Science; Science (multidisciplinary); Signal Processing, Computer-Assisted; Vital signs; Bandpass filtering; Vital signs; Millimeter wave; Heartbeat signals
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-025-86438-5

Heart disease is a significant global health issue. Traditional methods for heart rate monitoring typically require close physical contact, which limits the continuity and convenience of monitoring. To achieve real-time, non-contact heartbeat monitoring, researchers have introduced millimeter-wave radar technology. The technology’s penetration and privacy offer a potential solution for heart condition monitoring. Therefore, this study utilized frequency-modulated continuous wave (FMCW) radar for heart rate monitoring. Firstly, the collected millimeter-wave radar signals were preprocessed to accurately locate the area of cardiac activity in the human body. Secondly, an adaptive variational mode decomposition (A-VMD) algorithm was designed to extract the heartbeat signal, considering signal variations caused by random body movements and respiration and their harmonics, to obtain an accurate heartbeat signal. Finally, the accurate heart rate is obtained by weighted estimation based on the harmonic relationship of the heartbeat signal. The study invited ten subjects to participate in the experiment to verify the effectiveness of this method. The results show that this method can reduce the influence of and random body movements and respiration and harmonics on heart rate monitoring, the average absolute error of heart rate estimation is less than four bpm.