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

Emerging Technologies for Rehabilitation (348) Design and Usability of Medical Devices (141) Assistive Technologies (150) New Technologies (108) Robotics in Rehabilitation (59) Artificial Intelligence (2131) Reviews in AI (25)

Published on in Vol 12 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/69763, first published .
How AI-Based Digital Rehabilitation Improves End-User Adherence: Rapid Review

How AI-Based Digital Rehabilitation Improves End-User Adherence: Rapid Review

How AI-Based Digital Rehabilitation Improves End-User Adherence: Rapid Review

Authors of this article:

Mahsa MohammadNamdar1 Author Orcid Image ;   Michael Lowery Wilson1, 2 ;   Kari-Pekka Murtonen3 Author Orcid Image ;   Eeva Aartolahti3 Author Orcid Image ;   Michael Oduor3 Author Orcid Image ;   Katariina Korniloff3 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Mahsa MohammadNamdar   1 , MBA ;   Michael Lowery Wilson   1, 2 , PhD ;   Kari-Pekka Murtonen   3 , MSc ;   Eeva Aartolahti   3 , PhD ;   Michael Oduor   3 , PhD ;   Katariina Korniloff   3 , PhD

1 Injury Epidemiology and Prevention (IEP) Research Group, Turku Brain Injury Centre, Department of Clinical Neurosciences, Turku University Hospital and University of Turku, Turku, Finland

2 Section for Oral Health, Heidelberg Institute of Global Health (HIGH), Heidelberg University, Heidelberg, Germany

3 Institute of Rehabilitation, Jamk University of Applied Sciences, Jyväskylä, Finland

Corresponding Author:

  • Mahsa MohammadNamdar, MBA
  • Injury Epidemiology and Prevention (IEP) Research Group, Turku Brain Injury Centre
  • Department of Clinical Neurosciences, Turku University Hospital and University of Turku
  • Vähä Hämenkatu 2b
  • Turku 20500
  • Finland
  • Phone: 358 29 450 5000
  • Email: Mahsa.M.MohammadNamdar@utu.fi