Multimodal Photoplethysmography-Based Approaches for Improved Detection of Hypertension.

PPG signal biomedical engineering blood pressure measurement digital health digital medicine hypertension assessment hypertension diagnosis photoplethysmogram pulse arrival time pulse oximetry wearable devices wearable technology

Journal

Journal of clinical medicine
ISSN: 2077-0383
Titre abrégé: J Clin Med
Pays: Switzerland
ID NLM: 101606588

Informations de publication

Date de publication:
22 Apr 2020
Historique:
received: 09 03 2020
revised: 07 04 2020
accepted: 13 04 2020
entrez: 26 4 2020
pubmed: 26 4 2020
medline: 26 4 2020
Statut: epublish

Résumé

Elevated blood pressure (BP) is a major cause of death, yet hypertension commonly goes undetected. Owing to its nature, it is typically asymptomatic until later in its progression when the vessel or organ structure has already been compromised. Therefore, noninvasive and continuous BP measurement methods are needed to ensure appropriate diagnosis and early management before hypertension leads to irreversible complications. Photoplethysmography (PPG) is a noninvasive technology with waveform morphologies similar to that of arterial BP waveforms, therefore attracting interest regarding its usability in BP estimation. In recent years, wearable devices incorporating PPG sensors have been proposed to improve the early diagnosis and management of hypertension. Additionally, the need for improved accuracy and convenience has led to the development of devices that incorporate multiple different biosignals with PPG. Through the addition of modalities such as an electrocardiogram, a final measure of the pulse wave velocity is derived, which has been proved to be inversely correlated to BP and to yield accurate estimations. This paper reviews and summarizes recent studies within the period 2010-2019 that combined PPG with other biosignals and offers perspectives on the strengths and weaknesses of current developments to guide future advancements in BP measurement. Our literature review reveals promising measurement accuracies and we comment on the effective combinations of modalities and success of this technology.

Identifiants

pubmed: 32331360
pii: jcm9041203
doi: 10.3390/jcm9041203
pmc: PMC7230564
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

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Auteurs

Kaylie Welykholowa (K)

Faculty of Medicine, University of British Columbia, Vancouver, BC V6T 1Z3, Canada.

Manish Hosanee (M)

Faculty of Medicine, University of British Columbia, Vancouver, BC V6T 1Z3, Canada.

Gabriel Chan (G)

Faculty of Medicine, University of British Columbia, Vancouver, BC V6T 1Z3, Canada.

Rachel Cooper (R)

Faculty of Medicine, University of British Columbia, Vancouver, BC V6T 1Z3, Canada.

Panayiotis A Kyriacou (PA)

Research Centre for Biomedical Engineering, City, University of London, London EC1V 0HB, UK.

Dingchang Zheng (D)

Research Center of Intelligent Healthcare, Faculty of Health and Life Science, Coventry University, Coventry CV1 5FB, UK.

John Allen (J)

Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne NE2 4AX, UK.

Derek Abbott (D)

School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide SA 5005, Australia.
Centre for Biomedical Engineering, The University of Adelaide, Adelaide SA 5005, Australia.

Carlo Menon (C)

School of Mechatronic Systems Engineering, Simon Fraser University, Burnaby, BC V5A 1S6, Canada.

Nigel H Lovell (NH)

Graduate School of Biomedical Engineering, UNSW Sydney, Sydney NSW 2052, Australia.

Newton Howard (N)

Nuffield Department of Surgical Sciences, University of Oxford, Oxford OX3 9DU, UK.

Wee-Shian Chan (WS)

Faculty of Medicine, University of British Columbia, Vancouver, BC V6T 1Z3, Canada.

Kenneth Lim (K)

Faculty of Medicine, University of British Columbia, Vancouver, BC V6T 1Z3, Canada.

Richard Fletcher (R)

D-Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Department of Psychiatry, University of Massachusetts Medical School, Worcester, MA 01655, USA.

Rabab Ward (R)

School of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.

Mohamed Elgendi (M)

Faculty of Medicine, University of British Columbia, Vancouver, BC V6T 1Z3, Canada.
School of Mechatronic Systems Engineering, Simon Fraser University, Burnaby, BC V5A 1S6, Canada.
Nuffield Department of Surgical Sciences, University of Oxford, Oxford OX3 9DU, UK.
School of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.
BC Children's & Women's Hospital, Vancouver, BC V6H 3N1, Canada.

Classifications MeSH