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

Innovations in Exercise Rehabilitation (203) Machine Learning (1383) Exergames, Active Games and Gamification of Physical Activity (168)

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 (15) Tweetations (6) Metrics

Journals

  1. Joo S, Lee C, Joo N, Kim C. Feasibility and Effectiveness of a Motion Tracking-Based Online Fitness Program for Office Workers. Healthcare 2021;9(5):584 View
  2. Tuli A, Singh A. Polymer-based wearable nano-composite sensors: a review. International Journal of Polymer Analysis and Characterization 2023;28(2):156 View
  3. Fernandes C, Magalhães B, Gomes J, Santos C. Exergames to Improve Rehabilitation for Shoulder Injury: Systematic Review and GRADE Evidence Synthesis. Rehabilitation Nursing 2022;47(4):147 View
  4. Trombini M, Ferraro F, Iaconi G, Vestito L, Bandini F, Mori L, Trompetto C, Dellepiane S. A Study Protocol for Occupational Rehabilitation in Multiple Sclerosis. Sensors 2021;21(24):8436 View
  5. Tsakanikas V, Gatsios D, Pardalis A, Tsiouris K, Georga E, Bamiou D, Pavlou M, Nikitas C, Kikidis D, Walz I, Maurer C, Fotiadis D. Automated Assessment of Balance Rehabilitation Exercises With a Data-Driven Scoring Model: Algorithm Development and Validation Study. JMIR Rehabilitation and Assistive Technologies 2022;9(3):e37229 View
  6. Cunha B, Ferreira R, Sousa A. Home-Based Rehabilitation of the Shoulder Using Auxiliary Systems and Artificial Intelligence: An Overview. Sensors 2023;23(16):7100 View
  7. Kim J, Kim C, Xiang Y, Park J, Kang H, Song W, Lee H, Lee C, Ahn Y, Seo D. Effect of a Kinect-Based Exercise on Improving Job-Related Physical Fitness Tests for Korean Firefighters. The Asian Journal of Kinesiology 2023;25(3):30 View
  8. Weng X, Mei C, Gao F, Wu X, Zhang Q, Liu G. A gait stability evaluation method based on wearable acceleration sensors. Mathematical Biosciences and Engineering 2023;20(11):20002 View
  9. Wang Y. Understanding Senior Adults’ Needs, Preferences, and Experiences of Commercial Exergames for Health: Usability Study. JMIR Serious Games 2024;12:e36154 View
  10. Martinho D, Crista V, Carneiro J, Matsui K, Corchado J, Marreiros G. Effects of a Gamified Agent-Based System for Personalized Elderly Care: Pilot Usability Study. JMIR Serious Games 2023;11:e48063 View
  11. Wang H, Ma M. PhysiQ. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2022;6(4):1 View
  12. Lorenz E, Bråten Støen A, Lie Fridheim M, Alsos O. Design recommendations for XR-based motor rehabilitation exergames at home. Frontiers in Virtual Reality 2024;5 View
  13. Tuah N, Goh D, Nasirin S, Ahmedy F, Hossin M. Mapping Data Mining Technique and Gamification Approach for Studying Post-Stroke Rehabilitation Training: A Systematic Literature Review. IEEE Access 2023;11:31323 View
  14. Vakili Ojarood M, Yaghoubi T, Mohsenizadeh S, Torabi H, Farzan R. The future of burn management: How can machine learning lead to a revolution in improving the rehabilitation of burn patients?. Burns 2024;50(6):1704 View