Cuffless Single-Site Photoplethysmography for Blood Pressure Monitoring

Manish Hosanee, Gabriel Chan, Kaylie Welykholowa, Rachel Cooper, Panayiotis A Kyriacou, Dingchang Zheng, John Allen, Derek Abbott, Carlo Menon, Nigel H Lovell, Newton Howard, Wee-Shian Chan, Kenneth Lim, Richard Fletcher, Rabab Ward, Mohamed Elgendi

    Research output: Contribution to journalReview articlepeer-review

    32 Citations (Scopus)
    5 Downloads (Pure)

    Abstract

    One in three adults worldwide has hypertension, which is associated with significant morbidity and mortality. Consequently, there is a global demand for continuous and non-invasive blood pressure (BP) measurements that are convenient, easy to use, and more accurate than the currently available methods for detecting hypertension. This could easily be achieved through the integration of single-site photoplethysmography (PPG) readings into wearable devices, although improved reliability and an understanding of BP estimation accuracy are essential. This review paper focuses on understanding the features of PPG associated with BP and examines the development of this technology over the 2010-2019 period in terms of validation, sample size, diversity of subjects, and datasets used. Challenges and opportunities to move single-site PPG forward are also discussed.

    Original languageEnglish
    Article number723
    Number of pages14
    JournalJournal of Clinical Medicine
    Volume9
    Issue number3
    DOIs
    Publication statusPublished - 7 Mar 2020

    Bibliographical note

    This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution
    (CC BY) license (http://creativecommons.org/licenses/by/4.0/)

    Keywords

    • photoplethysmogram
    • photoplethysmography
    • PPG signal
    • hypertension assessment
    • hypertension diagnosis
    • blood pressure measurement
    • digital health
    • digital medicine
    • wearable technology
    • wearable devices
    • pulse oximetry
    • biomedical engineering
    • biomedical signal analysis

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