Blood pressure estimation from photoplethysmogram and electrocardiogram signals using machine learning

Sen Yang, Wan S.W. Zaki, Stephen P. Morgan, Siu Yeung Cho, Ricardo Correia, Long Wen, Yaping Zhang

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)
62 Downloads (Pure)

Abstract

Blood pressure measurement is a significant part of preventive healthcare and has been widely used in clinical risk and disease management. However, conventional measurement does not provide continuous monitoring and sometimes is inconvenient with a cuff. In addition to the traditional cuff-based blood pressure measurement methods, some researchers have developed various cuff-less and noninvasive blood pressure monitoring methods based on Pulse Transit Time (PTT). Some emerging methods have employed features of either photoplethysmogram (PPG) or electrocardiogram (ECG) signals, although no studies to our knowledge have employed the combined features from both PPG and ECG signals. Therefore this study aims to investigate the performance of a predictive, machine learning blood pressure monitoring system using both PPG and ECG signals. It validates that the employment of the combination of PPG and ECG signals has improved the accuracy of the blood pressure estimation, compared with previously reported results based on PPG signal only.

Original languageEnglish
Title of host publicationIET Doctoral Forum on Biomedical Engineering, Healthcare, Robotics and Artificial Intelligence 2018, BRAIN 2018
PublisherInstitution of Engineering and Technology
EditionCP754
ISBN (Print)9781785617911, 9781839530838
DOIs
Publication statusPublished - 2018
EventIET Doctoral Forum on Biomedical Engineering, Healthcare, Robotics and Artificial Intelligence 2018, BRAIN 2018 - Ningbo, China
Duration: 4 Nov 2018 → …

Publication series

NameIET Conference Publications
NumberCP754
Volume2018

Conference

ConferenceIET Doctoral Forum on Biomedical Engineering, Healthcare, Robotics and Artificial Intelligence 2018, BRAIN 2018
Country/TerritoryChina
CityNingbo
Period4/11/18 → …

Keywords

  • BLOOD PRESSURE
  • ELECTROCARDIOGRAM (ECG)
  • FEATURES
  • PHOTOPLETHYSMOGRAM (PPG)

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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