Your browser doesn't support javascript.
loading
Recommendations for evaluating photoplethysmography-based algorithms for blood pressure assessment.
Elgendi, Mohamed; Haugg, Fridolin; Fletcher, Richard Ribon; Allen, John; Shin, Hangsik; Alian, Aymen; Menon, Carlo.
Affiliation
  • Elgendi M; Biomedical and Mobile Health Technology Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, 8008, Switzerland. moe.elgendi@hest.ethz.ch.
  • Haugg F; Biomedical and Mobile Health Technology Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, 8008, Switzerland.
  • Fletcher RR; Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
  • Allen J; Research Centre for Intelligent Healthcare, Coventry University, CV1 5FB, Coventry, UK.
  • Shin H; Department of Convergence Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, 05505, Republic of Korea.
  • Alian A; Yale School of Medicine, Yale University, New Haven, CT, 06510, USA.
  • Menon C; Biomedical and Mobile Health Technology Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, 8008, Switzerland.
Commun Med (Lond) ; 4(1): 140, 2024 Jul 12.
Article in En | MEDLINE | ID: mdl-38997447
ABSTRACT
Photoplethysmography (PPG) is a non-invasive optical technique that measures changes in blood volume in the microvascular tissue bed of the body. While it shows potential as a clinical tool for blood pressure (BP) assessment and hypertension management, several sources of error can affect its performance. One such source is the PPG-based algorithm, which can lead to measurement bias and inaccuracy. Here, we review seven widely used measures to assess PPG-based algorithm performance and recommend implementing standardized error evaluation steps in their development. This standardization can reduce bias and improve the reliability and accuracy of PPG-based BP estimation, leading to better health outcomes for patients managing hypertension.

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Commun Med (Lond) Year: 2024 Document type: Article Affiliation country: Suiza Country of publication: Reino Unido

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Commun Med (Lond) Year: 2024 Document type: Article Affiliation country: Suiza Country of publication: Reino Unido