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The Accuracy of Wearable Photoplethysmography Sensors for Telehealth Monitoring: A Scoping Review.
Knight, Sheida; Lipoth, Jessica; Namvari, Mina; Gu, Carol; Hedayati Ch, Mojtaba; Syed-Abdul, Shabbir; Spiteri, Raymond J.
  • Knight S; Department of Computer Science, University of Saskatchewan, Saskatoon, Saskatchewan, Canada.
  • Lipoth J; Department of Computer Science, University of Saskatchewan, Saskatoon, Saskatchewan, Canada.
  • Namvari M; Department of Computer Science, University of Saskatchewan, Saskatoon, Saskatchewan, Canada.
  • Gu C; Center for Bio-Integrated Electronics at Northwestern University, Evanston, Illinois, USA.
  • Hedayati Ch M; Guilan University of Medical Sciences, Rasht, Guilan, Iran.
  • Syed-Abdul S; Graduate Institute of Biomedical Informatics, Taipei Medical University, Taipei, Taiwan.
  • Spiteri RJ; Department of Computer Science, University of Saskatchewan, Saskatoon, Saskatchewan, Canada.
Telemed J E Health ; 2022 Oct 25.
Article in English | MEDLINE | ID: covidwho-20238037
ABSTRACT
Background and

Objectives:

Photoplethysmography (PPG) sensors have been increasingly used for remote patient monitoring, especially during the COVID-19 pandemic, for the management of chronic diseases and neurological disorders. There is an urgent need to evaluate the accuracy of these devices. This scoping review considers the latest applications of wearable PPG sensors with a focus on studies that used wearable PPG sensors to monitor various health parameters. The primary objective is to report the accuracy of the PPG sensors in both real-world and clinical settings.

Methods:

This scoping review was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA). Studies were identified by querying the Medline, Embase, IEEE, and CINAHL databases. The goal was to capture eligible studies that used PPG sensors to monitor various health parameters for populations with a minimum of 30 participants, with at least some of the population having relevant health issues. A total of 2,996 articles were screened and 28 are included in this review.

Results:

The health parameters and disorders identified and investigated in this study include heart rate and heart rate variability, atrial fibrillation, blood pressure (BP), obstructive sleep apnea, blood glucose, heart failure, and respiratory rate. An overview of the algorithms used, and their limitations is provided.

Conclusion:

Some of the barriers identified in evaluating the accuracy of multiple types of wearable devices include the absence of reporting standard accuracy metrics and a general paucity of studies with large subject size in real-world settings, especially for parameters such as BP.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study / Reviews / Systematic review/Meta Analysis Language: English Journal subject: Medical Informatics / Health Services Year: 2022 Document Type: Article Affiliation country: Tmj.2022.0182

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Experimental Studies / Prognostic study / Reviews / Systematic review/Meta Analysis Language: English Journal subject: Medical Informatics / Health Services Year: 2022 Document Type: Article Affiliation country: Tmj.2022.0182