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

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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.
Original languageEnglish
Article number111001
Number of pages89
JournalPhysiological Measurement
Volume44
Issue number11
DOIs
Publication statusPublished - 29 Nov 2023

Bibliographical note

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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.

Keywords

  • blood pressure
  • cardiovascular
  • fitness
  • physiological monitoring
  • sensor
  • signal processing
  • smartwatch

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