Mohamed Elgendi, Fridolin Haugg, Richard Ribon Fletcher, John Allen, Hangsik Shin, Aymen Alian, Carlo Menon
{"title":"Recommendations for evaluating photoplethysmography-based algorithms for blood pressure assessment","authors":"Mohamed Elgendi, Fridolin Haugg, Richard Ribon Fletcher, John Allen, Hangsik Shin, Aymen Alian, Carlo Menon","doi":"10.1038/s43856-024-00555-2","DOIUrl":null,"url":null,"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. Elgendi et al. discuss pros and cons of seven measures to assess photoplethysmography-based algorithm performance for blood pressure estimation. They highlight the need for standardized error evaluation to enhance accuracy and reliability in hypertension management and make recommendations to achieve this goal.","PeriodicalId":72646,"journal":{"name":"Communications medicine","volume":null,"pages":null},"PeriodicalIF":5.4000,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s43856-024-00555-2.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communications medicine","FirstCategoryId":"1085","ListUrlMain":"https://www.nature.com/articles/s43856-024-00555-2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
引用次数: 0
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. Elgendi et al. discuss pros and cons of seven measures to assess photoplethysmography-based algorithm performance for blood pressure estimation. They highlight the need for standardized error evaluation to enhance accuracy and reliability in hypertension management and make recommendations to achieve this goal.