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DING Lingna, ZHANG Binbin, WANG Jianyang, et al. Driver heartbeat sensing using millimeter-wave radar based on deep blind source separation[J]. Journal of Radars, in press. doi: 10.12000/JR26042
Citation: DING Lingna, ZHANG Binbin, WANG Jianyang, et al. Driver heartbeat sensing using millimeter-wave radar based on deep blind source separation[J]. Journal of Radars, in press. doi: 10.12000/JR26042
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Driver Heartbeat Sensing Using Millimeter-wave Radar Based on Deep Blind Source Separation

DOI: 10.12000/JR26042 CSTR: 32380.14.JR26042

  • School of Cyber Science and Technology, University of Science and Technology of China, Hefei 230026, China

Funds:  The National Natural Science Foundation of China (62201542), The Fundamental Research Funds for the Central Universities
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  • Corresponding author: ZHANG Dongheng, dongheng@ustc.edu.cn
  • Received Date: 2026-02-09
  • Rev Recd Date: 2026-05-12
    • Available Online: 2026-05-15
    Abstract
  • Monitoring of drivers’ cardiac activity enables effective assessment of their physiological and psychological states. However, existing methods such as electrocardiography and remote phontoplethysmograyhy are cumbersome and sensitive to lighting conditions, limiting their applicability in vehicular settings. Despite its high accuracy and noncontact operation, millimeter-wave radar-based heartbeat sensing is inherently vulnerable to interference. To address these issues, this paper exploits the low-frequency characteristics, long-range dynamic sensitivity, and sparsity of Radio-Frequency (RF) signals and designs a self-attention-based RF feature extractor. On this basis, a deep blind source separation network is constructed to separate the driver’s heartbeat-related RF features from in-vehicle interference. Furthermore, to reduce the burden of RF signal acquisition, we introduce a hybrid-source signal generation strategy that synthesizes a large number of mixed and ground-truth source signals using only a small number of seismocardiogram and interference signals. Finally, extensive on-road testing demonstrates that the proposed system achieves a median heart rate error of 4.92 bpm and a median interbeat interval error of 65.93 ms.

     

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