Blood Pressure Estimation Using Photoplethysmography Only: Comparison between Different Machine Learning Approaches.

Journal: Journal of healthcare engineering
Published Date:

Abstract

INTRODUCTION: Blood pressure (BP) has been a potential risk factor for cardiovascular diseases. BP measurement is one of the most useful parameters for early diagnosis, prevention, and treatment of cardiovascular diseases. At present, BP measurement mainly relies on cuff-based techniques that cause inconvenience and discomfort to users. Although some of the present prototype cuffless BP measurement techniques are able to reach overall acceptable accuracies, they require an electrocardiogram (ECG) and a photoplethysmograph (PPG) that make them unsuitable for true wearable applications. Therefore, developing a single PPG-based cuffless BP estimation algorithm with enough accuracy would be clinically and practically useful.

Authors

  • Syed Ghufran Khalid
    Faculty of Medical Science, Anglia Ruskin University, Bishop Hall Ln, Chelmsford CM11SQ, UK.
  • Jufen Zhang
    Faculty of Medical Science, Anglia Ruskin University, Bishop Hall Ln, Chelmsford CM11SQ, UK.
  • Fei Chen
    Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China.
  • Dingchang Zheng
    Research Centre of Intelligent Healthcare, Coventry University, Coventry, United Kingdom.