The 2023 wearable photoplethysmography roadmap

Peter H. Charlton; John Allen; Raquel  Bailon; Stephanie  Baker; Joachim A  Behar; Fei Chen; Gari D  Clifford; David A Clifton; Harry J  Davies; Cheng   Ding; Xiaorong Ding; Jessilyn  Dunn; Mohamed Elgendi; Munia  Ferdoushi; Daniel   Franklin; Eduardo  Gil; Md Farhad  Hassan; Jussi  Hernesniemi; Xiao Hu; Nan Ji; Yasser  Khan; Spyridon  Kontaxis; Ilkka  Korhonen; Panayiotis A Kyriacou; Pablo  Laguna; Jesus  Lazaro; Chungkeun  Lee; Jeremy  Levy; Yumin Li; Chengyu Liu; Jing  Liu; Lei  Lu; Danilo P  Mandic; Vaidotas Marozas; Elisa Mejia-Mejia; Ramakrishna  Mukkamala; Meir   Nitzan; Tânia   Pereira; Carmen C Y  Poon; Jessica C  Ramella-Roman; Harri  Saarinen; Md Mobashir Hasan  Shandhi; Hangsik  Shin; Gerard Stansby; Toshiyo  Tamura; Antti  Vehkaoja; Will Ke  Wang; Yuan-Ting  Zhang; Ni  Zhao; Dingchang Zheng; Tingting Zhu

doi:10.1088/1361-6579/acead2

The 2023 wearable photoplethysmography roadmap

Peter H. Charlton, John Allen, Raquel Bailon, Stephanie Baker, Joachim A Behar, Fei Chen, Gari D Clifford, David A Clifton, Harry J Davies, Cheng Ding, Xiaorong Ding, Jessilyn Dunn, Mohamed Elgendi, Munia Ferdoushi, Daniel Franklin, Eduardo Gil, Md Farhad Hassan, Jussi Hernesniemi, Xiao Hu, Nan JiYasser Khan, Spyridon Kontaxis, Ilkka Korhonen, Panayiotis A Kyriacou, Pablo Laguna, Jesus Lazaro, Chungkeun Lee, Jeremy Levy, Yumin Li, Chengyu Liu, Jing Liu, Lei Lu, Danilo P Mandic, Vaidotas Marozas, Elisa Mejia-Mejia, Ramakrishna Mukkamala, Meir Nitzan, Tânia Pereira, Carmen C Y Poon, Jessica C Ramella-Roman, Harri Saarinen, Md Mobashir Hasan Shandhi, Hangsik Shin, Gerard Stansby, Toshiyo Tamura, Antti Vehkaoja, Will Ke Wang, Yuan-Ting Zhang, Ni Zhao, Dingchang Zheng, Tingting Zhu

Centre for Intelligent Healthcare

Research output: Contribution to journal › Article › peer-review

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336 Downloads (Pure)

Abstract

Photoplethysmography is a key sensing technology which is used in wearable devices such as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to monitor physiological parameters including heart rate and heart rhythm, and to track activities like sleep and exercise. Yet, wearable photoplethysmography has potential to provide much more information on health and wellbeing, which could inform clinical decision making. This Roadmap outlines directions for research and development to realise the full potential of wearable photoplethysmography. Experts discuss key topics within the areas of sensor design, signal processing, clinical applications, and research directions. Their perspectives provide valuable guidance to researchers developing wearable photoplethysmography technology.

Original language	English
Article number	111001
Number of pages	89
Journal	Physiological Measurement
Volume	44
Issue number	11
DOIs	https://doi.org/10.1088/1361-6579/acead2
Publication status	Published - 29 Nov 2023

Bibliographical note

CC-BY
Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.

Funder

This work was supported by the British Heart Foundation under Grant FS/20/20/34626, and COST Action CA18216 VascAgeNet, supported by COST (European Cooperation in Science and Technology, www.cost.eu).
They authors give special thanks to the UKRI PhD scholarship funding, and support from the MURI/EPSRC grant EP/P008461.
The authors acknowledge financial support from General Research Fund (RGC Ref No. 14209620) from the Research Grants Council of Hong Kong.
PHC acknowledges funding from the British Heart Foundation (FS/20/20/34626) and an EPSRC Impact Acceleration Award. JL acknowloedges funding from CIBER in Bioengineering, Biomaterials & Nanomedicine through Instituto de Salud Carlos III and by Gobierno de Aragon (Reference Group BSICoS T39-20R) cofunded by the Fondo Europeo de Desarrollo Regional (FEDER) 2014–2020 'Building Europe from Aragon'.
This work was supported by the European Regional Development Fund with the 'Ministerio de Ciencia e Innovación' of Spain under project PID2021-126734OB-C21 and with the Research Council of Lithuania (LMTLT) under Projects 01.2.2-LMT-K-718-01-0030 and 01.2.2-LMT-K-718-03-0027, the European COST ACTION 'Network for Research in Vascular Ageing' CA18216 supported by COST (European Cooperation in Science and Technology): www.cost.eu.
This work was supported in part by grants-in-aid from the Japanese Ministry of Education, Culture, Sports, Science and Technology, Scientific Research (C) (Kakenhi) (#21K12760) and the Japan Agency for Medical Research and Development (JP22dk0310111).
This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HR20C0026, HI22C1668).
This work was partially funded by the National Center for Advancing Translational Sciences of the National Institutes of Health under Award Number UL1TR002378 and the NIMH under Award Number U01MH110925.
The work was supported by CIBER in Bioengineering, Biomaterials & Nanomedicne (CIBERBBN) through Instituto de Salud Carlos III, FEDER and Gobierno de Aragon (BSICoS T39-20R).
This work is supported by Sichuan Science and Technology Program (2021YFH0179) and InnoHK scheme by ITC.
The research was supported by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC) and by the Hong Kong Centre for Cerebro-cardiovascular Health Engineering (COCHE) funded by the Hong Kong ITC. The views expressed are those of the authors and not necessarily those of InnoHK-ITC. TZ was supported by the Royal Academy of Engineering under the Research Fellowship scheme. DAC acknowledges support from the Oxford Suzhou Centre for Advanced Research (OSCAR). DAC was supported by a Royal Academy of Engineering Research Chair; an NIHR Research Professorship; the NIHR Oxford Biomedical Research Centre; and the InnoHK Hong Kong Centre for Centre for Cerebro-cardiovascular Engineering (COCHE). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, the Department of Health or ITC.
This work was supported by the US National Institutes of Health Grant HL146470.
Dr Ramella-Roman acknowledges the support of the National Science Foundation Engineering Research Center for Precise Advanced Technologies and Health Systems for Underserved Populations (PATHS-UP) (#1648451).
PHC acknowledges funding from the British Heart Foundation (FS/20/20/34626).

Funding

This work was supported by the British Heart Foundation under Grant FS/20/20/34626, and COST Action CA18216 VascAgeNet, supported by COST (European Cooperation in Science and Technology, www.cost.eu). They authors give special thanks to the UKRI PhD scholarship funding, and support from the MURI/EPSRC grant EP/P008461. The authors acknowledge financial support from General Research Fund (RGC Ref No. 14209620) from the Research Grants Council of Hong Kong. PHC acknowledges funding from the British Heart Foundation (FS/20/20/34626) and an EPSRC Impact Acceleration Award. JL acknowloedges funding from CIBER in Bioengineering, Biomaterials & Nanomedicine through Instituto de Salud Carlos III and by Gobierno de Aragon (Reference Group BSICoS T39-20R) cofunded by the Fondo Europeo de Desarrollo Regional (FEDER) 2014–2020 'Building Europe from Aragon'. This work was supported by the European Regional Development Fund with the 'Ministerio de Ciencia e Innovación' of Spain under project PID2021-126734OB-C21 and with the Research Council of Lithuania (LMTLT) under Projects 01.2.2-LMT-K-718-01-0030 and 01.2.2-LMT-K-718-03-0027, the European COST ACTION 'Network for Research in Vascular Ageing' CA18216 supported by COST (European Cooperation in Science and Technology): www.cost.eu. This work was supported in part by grants-in-aid from the Japanese Ministry of Education, Culture, Sports, Science and Technology, Scientific Research (C) (Kakenhi) (#21K12760) and the Japan Agency for Medical Research and Development (JP22dk0310111). This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HR20C0026, HI22C1668). This work was partially funded by the National Center for Advancing Translational Sciences of the National Institutes of Health under Award Number UL1TR002378 and the NIMH under Award Number U01MH110925. The work was supported by CIBER in Bioengineering, Biomaterials & Nanomedicne (CIBERBBN) through Instituto de Salud Carlos III, FEDER and Gobierno de Aragon (BSICoS T39-20R). This work is supported by Sichuan Science and Technology Program (2021YFH0179) and InnoHK scheme by ITC. The research was supported by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC) and by the Hong Kong Centre for Cerebro-cardiovascular Health Engineering (COCHE) funded by the Hong Kong ITC. The views expressed are those of the authors and not necessarily those of InnoHK-ITC. TZ was supported by the Royal Academy of Engineering under the Research Fellowship scheme. DAC acknowledges support from the Oxford Suzhou Centre for Advanced Research (OSCAR). DAC was supported by a Royal Academy of Engineering Research Chair; an NIHR Research Professorship; the NIHR Oxford Biomedical Research Centre; and the InnoHK Hong Kong Centre for Centre for Cerebro-cardiovascular Engineering (COCHE). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, the Department of Health or ITC. This work was supported by the US National Institutes of Health Grant HL146470. Dr Ramella-Roman acknowledges the support of the National Science Foundation Engineering Research Center for Precise Advanced Technologies and Health Systems for Underserved Populations (PATHS-UP) (#1648451). PHC acknowledges funding from the British Heart Foundation (FS/20/20/34626).

Funders	Funder number
British Heart Foundation	FS/20/20/34626
EU Cost Action - VascAgeNet	CA18216
Engineering and Physical Sciences Research Council	EP/P008461
Research Grants Council of Hong Kong	14209620
Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina
Fondo Europeo de Desarrollo Regional
European Regional Development Fund
Ministerio de Ciencia e Innovación	PID2021-126734OB-C21
Research Council of Lithuania	01.2.2-LMT-K-718-01-0030, 01.2.2-LMT-K-718-03-0027
Ministry of Education, Culture, Sports, Science and Technology	21K12760
Japan Agency for Medical Research and Development	JP22dk0310111
Ministry of Health and Welfare	HR20C0026, HI22C1668
National Institutes of Health	UL1TR002378, HL146470
National Institute of Mental Health	U01MH110925
Gobierno de Aragon	BSICoS T39-20R
Sichuan Science and Technology Program	2021YFH0179
Innovation and Technology Commission
Oxford NIHR Biomedical Research Centre
Royal Academy of Engineering, The
Oxford Suzhou Centre for Advanced Research
National Science Foundation	1648451

Keywords

blood pressure
cardiovascular
fitness
physiological monitoring
sensor
signal processing
smartwatch

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10.1088/1361-6579/acead2Licence: CC BY

Charlton+et+al_2023_Physiol._Meas._10.1088_1361-6579_acead2Accepted author manuscript, 4.85 MBLicence: CC BY
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Cite this

Charlton, P. H., Allen, J., Bailon, R., Baker, S., Behar, J. A., Chen, F., Clifford, G. D., Clifton, D. A., Davies, H. J., Ding, C., Ding, X., Dunn, J., Elgendi, M., Ferdoushi, M., Franklin, D., Gil, E., Hassan, M. F., Hernesniemi, J., Hu, X., ... Zhu, T. (2023). The 2023 wearable photoplethysmography roadmap. Physiological Measurement, 44(11), Article 111001. https://doi.org/10.1088/1361-6579/acead2

Charlton, PH, Allen, J, Bailon, R, Baker, S, Behar, JA, Chen, F, Clifford, GD, Clifton, DA, Davies, HJ, Ding, C, Ding, X, Dunn, J, Elgendi, M, Ferdoushi, M, Franklin, D, Gil, E, Hassan, MF, Hernesniemi, J, Hu, X, Ji, N, Khan, Y, Kontaxis, S, Korhonen, I, Kyriacou, PA, Laguna, P, Lazaro, J, Lee, C, Levy, J, Li, Y, Liu, C, Liu, J, Lu, L, Mandic, DP, Marozas, V, Mejia-Mejia, E, Mukkamala, R, Nitzan, M, Pereira, T, Poon, CCY, Ramella-Roman, JC, Saarinen, H, Shandhi, MMH, Shin, H, Stansby, G, Tamura, T, Vehkaoja, A, Wang, WK, Zhang, Y-T, Zhao, N, Zheng, D & Zhu, T 2023, 'The 2023 wearable photoplethysmography roadmap', Physiological Measurement, vol. 44, no. 11, 111001. https://doi.org/10.1088/1361-6579/acead2

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abstract = "Photoplethysmography is a key sensing technology which is used in wearable devices such as smartwatches and fitness trackers. Currently, photoplethysmography sensors are used to monitor physiological parameters including heart rate and heart rhythm, and to track activities like sleep and exercise. Yet, wearable photoplethysmography has potential to provide much more information on health and wellbeing, which could inform clinical decision making. This Roadmap outlines directions for research and development to realise the full potential of wearable photoplethysmography. Experts discuss key topics within the areas of sensor design, signal processing, clinical applications, and research directions. Their perspectives provide valuable guidance to researchers developing wearable photoplethysmography technology.",

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The 2023 wearable photoplethysmography roadmap

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