RadarNet: Noncontact ECG Signal Measurement Based on FMCW Radar

被引:0
|
作者
Li, Bin [1 ]
Li, Wenlong [2 ]
He, Yuchen [3 ,4 ]
Zhang, Wei [2 ]
Fu, Hong [5 ]
机构
[1] Xi An Jiao Tong Univ, Bioinspired Engn & Biomech Ctr BEBC, Sch Life Sci & Technol, Minist Educ,Key Lab Biomed Informat Engn, Xian 710049, Peoples R China
[2] Northwest Univ, Sch Informat Sci & Technol, Xian 98033, Peoples R China
[3] Xi An Jiao Tong Univ, Sch Elect Sci & Engn, Minist Educ, Key Lab,Elect Mat Res Lab, Xian 710049, Peoples R China
[4] Xi An Jiao Tong Univ, Int Ctr Dielect Res, Sch Elect Sci & Engn, Xian 710049, Peoples R China
[5] Educ Univ Hong Kong, Dept Math & Informat Technol, Hong Kong, Peoples R China
关键词
Electrocardiography; Radar; Monitoring; Biomedical monitoring; Radar measurements; Frequency measurement; Ultra wideband radar; Heart rate; Time-frequency analysis; Filtering; Electrocardiogram (ECG) signal measurement; frequency-modulated continuous wave (FMCW) radar; micromotion signal disentanglement; noncontact health monitor;
D O I
10.1109/TIM.2024.3476545
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Continuous monitoring of electrocardiogram (ECG) signals plays an important role in the prevention and diagnosis of cardiovascular diseases. Conventional ECG signal measurement requires skin-contact electrodes, which are unfriendly to skin sensitive, burn patients and infants. In this article, we propose a noncontact ECG signal measurement method based on frequency-modulated continuous wave (FMCW) radar, facilitated by a signal amplification network named RadarNet. First, a multidomain joint modulation micromotion signal disentanglement module (MSDM) is introduced to extract cardiac mechanical motion (CMM) signals from complex radar waveforms. Then, a signal reconstruction network RadarNet based on time-frequency domain transformation is proposed to learn the nonlinear relationship between CMM and ECG signal. Finally, the first annotated dataset with synchronized FMCW radar-physiological signal RadarPhys-30 is established, which contains 30 subjects in two physiological states (sitting and lying down). The experimental results on the RadarPhys-30 dataset demonstrate that the mean average error (MAE) and the root-mean-square error (RMSE) of the heart rate (HR) estimated from the reconstructed ECG signal are less than 0.20 beats per minute (bpm) and 0.53 bpm in the sitting state, and 0.15 and 0.46 bpm in the lying down state, respectively. These results indicate that the proposed method achieves accurate noncontact ECG signal monitoring.
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页数:9
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