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Contactless HR monitoring and HRV assessment by attention-based fusion using a continuous wave radar system
Citation Link: https://doi.org/10.15480/882.17686
Publikationstyp
Journal Article
Date Issued
2026-07-14
Sprache
English
Author(s)
TORE-DOI
Journal
Volume
14
Start Page
108098
End Page
108113
Citation
IEEE Access 14: 108098-108113 (2026)
Publisher DOI
Scopus ID
Publisher
IEEE
Continuous wave (CW) radar is an alternative to gold-standard electrocardiography (ECG) for contactless heart rate (HR) monitoring and heart rate variability (HRV) analysis. This work aims to monitor HR and HRV using a deep learning (DL) model with a 61 GHz CW radar system. We employed attention-based DL fusion model to combine information from radar heart sound (HS) and radar pulse wave (PW) signals. Additionally, we compared attention-based fusion with alternative fusion methods, including data fusion, feature fusion, and decision fusion. To evaluate the performance of the proposed method, a dataset of approximately 20 hours was collected from 20 participants in varying body positions. Using attention-based fusion, we achieved the overall highest F1 score of 97.15% for heartbeat detection, which outperformed solely HS-based or PW-based model, as well as other fusion methods. F1 scores exceeding 96% were obtained for all analyzed body positions. A high correlation of 97.11% and an RMSE of 28.99 ms were achieved for the estimation of the interbeat interval (IBI). In addition, we extracted HRV in time, frequency, and nonlinear domains. Low relative errors were achieved, e.g. 14.04% for TRI, 6.14% for LF, 6.35% for alpha2, and 10.93% for ApEn. The proposed approach achieved high-level performance for HR monitoring and HRV estimation using a CW radar system, showing great potential for various healthcare applications.
Subjects
attention
CW radar
deep learning
fusion
heart rate
heart rate variability
heart sound
pulse wave
DDC Class
610: Medicine, Health
Publication version
publishedVersion
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Contactless_HR_Monitoring_and_HRV_Assessment_by_Attention-Based_Fusion_Using_a_Continuous_Wave_Radar_System.pdf
Type
Main Article
Size
3.32 MB
Format
Adobe PDF