TY - JOUR
T1 - Recommendations for evaluating photoplethysmography-based algorithms for blood pressure assessment
AU - Elgendi, Mohamed
AU - Haugg, Fridolin
AU - Fletcher, Richard Ribon
AU - Allen, John
AU - Shin, Hangsik
AU - Alian, Aymen
AU - Menon, Carlo
N1 - Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
PY - 2024/7/12
Y1 - 2024/7/12
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85204249254&partnerID=8YFLogxK
U2 - 10.1038/s43856-024-00555-2
DO - 10.1038/s43856-024-00555-2
M3 - Article
SN - 2730-664X
VL - 4
JO - Communications Medicine
JF - Communications Medicine
M1 - 140
ER -