This paper is in the following e-collection/theme issue:

Innovations in Exercise Rehabilitation (216) Machine Learning (1501) Exergames, Active Games and Gamification of Physical Activity (182)

Published on in Vol 7, No 2 (2020): Jul-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/17289, first published .
Rehabilitation Exergames: Use of Motion Sensing and Machine Learning to Quantify Exercise Performance in Healthy Volunteers

Rehabilitation Exergames: Use of Motion Sensing and Machine Learning to Quantify Exercise Performance in Healthy Volunteers

Rehabilitation Exergames: Use of Motion Sensing and Machine Learning to Quantify Exercise Performance in Healthy Volunteers

Authors of this article:

Reza Haghighi Osgouei1 Author Orcid Image ;   David Soulsby2 Author Orcid Image ;   Fernando Bello1 Author Orcid Image
Article Authors Cited by (16) Tweetations (6) Metrics

Reza Haghighi Osgouei   1 , PhD ;   David Soulsby   2 , BSc ;   Fernando Bello   1 , PhD

1 Imperial College Centre for Engagement and Simulation Science (ICCESS), Faculty of Medicine, Department of Surgery and Cancer, Imperial College London, London, United Kingdom

2 Children's Services and Dietetics, Chelsea and Westminster Hospital, London, United Kingdom

Corresponding Author:

  • Reza Haghighi Osgouei, PhD
  • Imperial College Centre for Engagement and Simulation Science (ICCESS)
  • Faculty of Medicine, Department of Surgery and Cancer
  • Imperial College London
  • Room H.3.8, ICCESS, Chelsea and Westminster
  • 369 Fulham Road
  • London, SW10 9NH
  • United Kingdom
  • Phone: 44 940419331
  • Email: r.haghighi-osgouei@imperial.ac.uk