TY - GEN
T1 - Feasibility of Radar-Based Heart Rate Variability Measurement
T2 - 15th IEEE Annual Computing and Communication Workshop and Conference, CCWC 2025
AU - Smiley, Aref
AU - Finkelstein, Joseph
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - This study evaluates the feasibility and accuracy of using radar-based, non-contact heart rate variability (HRV) measurements as an alternative to traditional electrocardiogram (ECG) methods. HRV metrics provide insights into autonomic nervous system activity and are typically obtained through contact-based sensors such as ECG, which require direct skin contact. This study collected HRV data from seven participants using a Biopac ECG system and a Texas Instruments IWR1443BOOST radar sensor. Each participant's data was recorded in three resting intervals, with HRV features extracted using Kubios HRV Scientific software. Key HRV metrics were analyzed and compared across both modalities, including time-domain features such as mean RR intervals, SDNN, RMSSD, and autonomic nervous system indices (PNS and SNS). The findings demonstrate that radar-derived HRV measurements are largely comparable to ECG measurements, with consistent mean RR intervals and heart rates observed across participants. However, the radar system exhibited higher variability in certain time-domain metrics, such as SDNN and RMSSD, suggesting increased sensitivity to specific physiological influences. Variations in PNS and SNS indices also indicated that radar may capture higher levels of parasympathetic activity. These results highlight the potential of radar-based HRV measurement as a practical alternative to traditional ECG, particularly in non-contact applications where direct skin contact is not feasible. Future studies aim to enhance the accuracy of radar-based HRV measurement and explore its potential in dynamic and clinical settings.
AB - This study evaluates the feasibility and accuracy of using radar-based, non-contact heart rate variability (HRV) measurements as an alternative to traditional electrocardiogram (ECG) methods. HRV metrics provide insights into autonomic nervous system activity and are typically obtained through contact-based sensors such as ECG, which require direct skin contact. This study collected HRV data from seven participants using a Biopac ECG system and a Texas Instruments IWR1443BOOST radar sensor. Each participant's data was recorded in three resting intervals, with HRV features extracted using Kubios HRV Scientific software. Key HRV metrics were analyzed and compared across both modalities, including time-domain features such as mean RR intervals, SDNN, RMSSD, and autonomic nervous system indices (PNS and SNS). The findings demonstrate that radar-derived HRV measurements are largely comparable to ECG measurements, with consistent mean RR intervals and heart rates observed across participants. However, the radar system exhibited higher variability in certain time-domain metrics, such as SDNN and RMSSD, suggesting increased sensitivity to specific physiological influences. Variations in PNS and SNS indices also indicated that radar may capture higher levels of parasympathetic activity. These results highlight the potential of radar-based HRV measurement as a practical alternative to traditional ECG, particularly in non-contact applications where direct skin contact is not feasible. Future studies aim to enhance the accuracy of radar-based HRV measurement and explore its potential in dynamic and clinical settings.
KW - ECG Comparison
KW - Heart Rate Variability (HRV)
KW - Non-Contact Monitoring
KW - Radar-Based HRV Measurement
UR - http://www.scopus.com/inward/record.url?scp=105001107262&partnerID=8YFLogxK
U2 - 10.1109/CCWC62904.2025.10903703
DO - 10.1109/CCWC62904.2025.10903703
M3 - Conference contribution
AN - SCOPUS:105001107262
T3 - 2025 IEEE 15th Annual Computing and Communication Workshop and Conference, CCWC 2025
SP - 376
EP - 379
BT - 2025 IEEE 15th Annual Computing and Communication Workshop and Conference, CCWC 2025
A2 - Paul, Rajashree
A2 - Kundu, Arpita
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 6 January 2025 through 8 January 2025
ER -