@article{ART003017315},
author={Yonghee Lee and YongWan Ju and Jundong Lee},
title={Artificial intelligence-based blood pressure prediction using photoplethysmography signals},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2023},
volume={28},
number={11},
pages={155-160},
doi={10.9708/jksci.2023.28.11.155}
TY - JOUR
AU - Yonghee Lee
AU - YongWan Ju
AU - Jundong Lee
TI - Artificial intelligence-based blood pressure prediction using photoplethysmography signals
JO - Journal of The Korea Society of Computer and Information
PY - 2023
VL - 28
IS - 11
PB - The Korean Society Of Computer And Information
SP - 155
EP - 160
SN - 1598-849X
AB - This paper presents a method for predicting blood pressure using the photoplethysmography signals.
First, after measuring the optical blood flow signal, artifacts are removed through a preprocessing process, and a signal for learning is obtained. In addition, weight and height, which affect blood pressure, are measured as additional information. Next, a system is built to estimate systolic and diastolic blood pressure by learning the photoplethysmography signals, height, and weight as input variables through an artificial intelligence algorithm. The constructed system predicts the systolic and diastolic blood pressures using the inputs. The proposed method can continuously predict blood pressure in real time by receiving photoplethysmography signals that reflect the state of the heart and blood vessels, and the height and weight of the subject in an unconstrained method. In order to confirm the usefulness of the artificial intelligence-based blood pressure prediction system presented in this study, the usefulness of the results is verified by comparing the measured blood pressure with the predicted blood pressure.
KW - Blood Pressure;Artificial Intelligence;Photoplethysmography;Prediction System;Continuous Monitoring
DO - 10.9708/jksci.2023.28.11.155
ER -
Yonghee Lee, YongWan Ju and Jundong Lee. (2023). Artificial intelligence-based blood pressure prediction using photoplethysmography signals. Journal of The Korea Society of Computer and Information, 28(11), 155-160.
Yonghee Lee, YongWan Ju and Jundong Lee. 2023, "Artificial intelligence-based blood pressure prediction using photoplethysmography signals", Journal of The Korea Society of Computer and Information, vol.28, no.11 pp.155-160. Available from: doi:10.9708/jksci.2023.28.11.155
Yonghee Lee, YongWan Ju, Jundong Lee "Artificial intelligence-based blood pressure prediction using photoplethysmography signals" Journal of The Korea Society of Computer and Information 28.11 pp.155-160 (2023) : 155.
Yonghee Lee, YongWan Ju, Jundong Lee. Artificial intelligence-based blood pressure prediction using photoplethysmography signals. 2023; 28(11), 155-160. Available from: doi:10.9708/jksci.2023.28.11.155
Yonghee Lee, YongWan Ju and Jundong Lee. "Artificial intelligence-based blood pressure prediction using photoplethysmography signals" Journal of The Korea Society of Computer and Information 28, no.11 (2023) : 155-160.doi: 10.9708/jksci.2023.28.11.155
Yonghee Lee; YongWan Ju; Jundong Lee. Artificial intelligence-based blood pressure prediction using photoplethysmography signals. Journal of The Korea Society of Computer and Information, 28(11), 155-160. doi: 10.9708/jksci.2023.28.11.155
Yonghee Lee; YongWan Ju; Jundong Lee. Artificial intelligence-based blood pressure prediction using photoplethysmography signals. Journal of The Korea Society of Computer and Information. 2023; 28(11) 155-160. doi: 10.9708/jksci.2023.28.11.155
Yonghee Lee, YongWan Ju, Jundong Lee. Artificial intelligence-based blood pressure prediction using photoplethysmography signals. 2023; 28(11), 155-160. Available from: doi:10.9708/jksci.2023.28.11.155
Yonghee Lee, YongWan Ju and Jundong Lee. "Artificial intelligence-based blood pressure prediction using photoplethysmography signals" Journal of The Korea Society of Computer and Information 28, no.11 (2023) : 155-160.doi: 10.9708/jksci.2023.28.11.155
