@article{ART003266137},
author={Yonghee Lee and Jeonghwan Cha and Jundong Lee},
title={Biometric identification using artificial intelligence-based photoplethysmography signals},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2025},
volume={30},
number={11},
pages={277-281}
TY - JOUR
AU - Yonghee Lee
AU - Jeonghwan Cha
AU - Jundong Lee
TI - Biometric identification using artificial intelligence-based photoplethysmography signals
JO - Journal of The Korea Society of Computer and Information
PY - 2025
VL - 30
IS - 11
PB - The Korean Society Of Computer And Information
SP - 277
EP - 281
SN - 1598-849X
AB - In this study, In this study, we propose a method for personal identification using photoplethysmography (PPG) signals utilizing deep learning techniques. PPG signals are closely related to the anatomical structure and hemodynamic characteristics of the heart. Unlike electrocardiograms (ECGs), they do not require electrode attachment and can be easily measured noninvasively using optical sensors. In this study, we performed preprocessing on PPG signals measured at rest, followed by training and classification using a deep learning model. The results confirmed that individual identification is possible based on the characteristics of PPG signals corresponding to periodic cardiac and ventricular activity and changes in physical condition. The proposed method was evaluated by acquiring 610 periodic PPG signals from 12 subjects. The evaluation results verified the usefulness and applicability of the proposed approach.
KW - Biometric;Photoplethysmography;Electrocardiogram;PPG;Deep learning
DO -
UR -
ER -
Yonghee Lee, Jeonghwan Cha and Jundong Lee. (2025). Biometric identification using artificial intelligence-based photoplethysmography signals. Journal of The Korea Society of Computer and Information, 30(11), 277-281.
Yonghee Lee, Jeonghwan Cha and Jundong Lee. 2025, "Biometric identification using artificial intelligence-based photoplethysmography signals", Journal of The Korea Society of Computer and Information, vol.30, no.11 pp.277-281.
Yonghee Lee, Jeonghwan Cha, Jundong Lee "Biometric identification using artificial intelligence-based photoplethysmography signals" Journal of The Korea Society of Computer and Information 30.11 pp.277-281 (2025) : 277.
Yonghee Lee, Jeonghwan Cha, Jundong Lee. Biometric identification using artificial intelligence-based photoplethysmography signals. 2025; 30(11), 277-281.
Yonghee Lee, Jeonghwan Cha and Jundong Lee. "Biometric identification using artificial intelligence-based photoplethysmography signals" Journal of The Korea Society of Computer and Information 30, no.11 (2025) : 277-281.
Yonghee Lee; Jeonghwan Cha; Jundong Lee. Biometric identification using artificial intelligence-based photoplethysmography signals. Journal of The Korea Society of Computer and Information, 30(11), 277-281.
Yonghee Lee; Jeonghwan Cha; Jundong Lee. Biometric identification using artificial intelligence-based photoplethysmography signals. Journal of The Korea Society of Computer and Information. 2025; 30(11) 277-281.
Yonghee Lee, Jeonghwan Cha, Jundong Lee. Biometric identification using artificial intelligence-based photoplethysmography signals. 2025; 30(11), 277-281.
Yonghee Lee, Jeonghwan Cha and Jundong Lee. "Biometric identification using artificial intelligence-based photoplethysmography signals" Journal of The Korea Society of Computer and Information 30, no.11 (2025) : 277-281.
