Why the study?
Wearable photoplethysmography sensors are increasingly used for remote patient monitoring, but there was an urgent need to evaluate their accuracy in real-world and clinical settings.
Are wearable photoplethysmography (PPG) sensors accurate for monitoring health parameters in clinical and real-world settings?
Are wearable photoplethysmography (PPG) sensors accurate for monitoring health parameters in clinical and real-world settings?
While wearable PPG sensors show potential for monitoring various health parameters, their clinical utility is currently limited by a lack of standardized accuracy metrics and large-scale real-world validation.
Answers are grounded in this paper and cite their sources.
Further validation studies are required before PPG wearables can support routine telehealth; this review leaves open their accuracy for clinical use.
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.
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Lipoth et al. (2022) studied this question.
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