본문 바로가기
  • Home

Artificial intelligence-based blood pressure prediction using photoplethysmography signals

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2023, 28(11), pp.155-160
  • DOI : 10.9708/jksci.2023.28.11.155
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : October 4, 2023
  • Accepted : November 1, 2023
  • Published : November 30, 2023

Yonghee Lee 1 YongWan Ju 2 Jundong Lee 2

1한라대학교
2강릉원주대학교

Accredited

ABSTRACT

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.

Citation status

* References for papers published after 2022 are currently being built.

This paper was written with support from the National Research Foundation of Korea.