TY - GEN
T1 - A Smart Ring for Long-term Blood Pressure Monitoring
AU - Chen, Jiarong
AU - Wang, Min
AU - Liu, Bin
AU - Chen, Cheng
AU - Wang, Guoxing
N1 - Publisher Copyright:
© 2026 IEEE.
PY - 2026
Y1 - 2026
N2 - Traditional cuff-based blood pressure (BP) monitoring methods suffer from inherent limitations in user discomfort and intermittent measurement. In contrast, photoplethysmography (PPG)-based BP estimation provides a promising alternative. However, several critical challenges remain in PPG-based BP estimation. First, prior evidence indicates that finger-worn devices can yield signals with higher feasibility and quality than wrist-worn devices. Second, long-term variations in blood pressure have not been sufficiently investigated in this field. To address these challenges, this study develops a novel smart ring platform and collects samples to train and evaluate the proposed model. A large-scale dataset comprising 116,995 samples from 96 subjects is constructed to evaluate long-term performance. The trained model achieves mean absolute errors (MAE) of 11.20 mmHg for systolic blood pressure (SBP) and 7.51 mmHg for diastolic blood pressure (DBP). These results demonstrate that a smart ring provides a comfortable and practical solution for continuous blood pressure management in personalized healthcare.
AB - Traditional cuff-based blood pressure (BP) monitoring methods suffer from inherent limitations in user discomfort and intermittent measurement. In contrast, photoplethysmography (PPG)-based BP estimation provides a promising alternative. However, several critical challenges remain in PPG-based BP estimation. First, prior evidence indicates that finger-worn devices can yield signals with higher feasibility and quality than wrist-worn devices. Second, long-term variations in blood pressure have not been sufficiently investigated in this field. To address these challenges, this study develops a novel smart ring platform and collects samples to train and evaluate the proposed model. A large-scale dataset comprising 116,995 samples from 96 subjects is constructed to evaluate long-term performance. The trained model achieves mean absolute errors (MAE) of 11.20 mmHg for systolic blood pressure (SBP) and 7.51 mmHg for diastolic blood pressure (DBP). These results demonstrate that a smart ring provides a comfortable and practical solution for continuous blood pressure management in personalized healthcare.
KW - Blood Pressure
KW - Personalized Healthcare
KW - Photoplethysmography
KW - Smart Ring
KW - Wear-able Device
UR - https://www.scopus.com/pages/publications/105043426554
U2 - 10.1109/ISCAS66217.2026.11562072
DO - 10.1109/ISCAS66217.2026.11562072
M3 - 会议稿件
AN - SCOPUS:105043426554
T3 - Proceedings - IEEE International Symposium on Circuits and Systems
SP - 3955
EP - 3959
BT - ISCAS 2026 - 2026 IEEE International Symposium on Circuits and Systems
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2026 IEEE International Symposium on Circuits and Systems, ISCAS 2026
Y2 - 24 May 2026 through 27 May 2026
ER -