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

Emerging Technologies for Rehabilitation (310) Human Factors and Usability Case Studies (914) Telerehabilitation (195) mHealth for Rehabilitation (320) Assistive Technologies (136)

Published on in Vol 10 (2023)

This is a member publication of Imperial College London (Jisc)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/45993, first published .
Examining Usability, Acceptability, and Adoption of a Self-Directed, Technology-Based Intervention for Upper Limb Rehabilitation After Stroke: Cohort Study

Examining Usability, Acceptability, and Adoption of a Self-Directed, Technology-Based Intervention for Upper Limb Rehabilitation After Stroke: Cohort Study

Examining Usability, Acceptability, and Adoption of a Self-Directed, Technology-Based Intervention for Upper Limb Rehabilitation After Stroke: Cohort Study

Authors of this article:

Michelle Broderick1 Author Orcid Image ;   Robert O'Shea2 Author Orcid Image ;   Jane Burridge3 Author Orcid Image ;   Sara Demain3 Author Orcid Image ;   Louise Johnson3, 4 Author Orcid Image ;   Paul Bentley1 Author Orcid Image
Article Authors Cited by (5) Tweetations (2) Metrics

Journals

  1. Jeter R, Greenfield R, Housley S, Belykh I. Classifying Residual Stroke Severity Using Robotics-Assisted Stroke Rehabilitation: Machine Learning Approach. JMIR Biomedical Engineering 2024;9:e56980 View
  2. Soulard J, Kairy D, Walha R, Duclos C, Nadeau S, Auger C. Professionals’ Perspectives of Smart Stationary Bikes in Rehabilitation: Qualitative Study. JMIR Rehabilitation and Assistive Technologies 2024;11:e64121 View
  3. Binyamin-Netser R, Handelzalts S, Goldhamer N, Avni I, Tayer Yeshurun A, Koren Y, Bibas Levy O, Kramer S, Bar Haim S, Shmuelof L. Neurotechnology-Based, Intensive, Supplementary Upper-Extremity Training for Inpatients With Subacute Stroke: Feasibility Study. JMIR Serious Games 2025;13:e56397 View

Conference Proceedings

  1. Mohd Dhuzuki N, Zainuddin A, Kamarudin S, Handayani D, Subramaniam K, Tamrin M. 2024 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET). Web-Based Medical Information System for Stroke Rehabilitation Intemet-of-Things (RIOT) Patients: A Prototype View
  2. Setyonugroho W, Utami S, Islami M, Amanu D, Kirana I, Fathiya A. 2024 Ninth International Conference on Informatics and Computing (ICIC). IoT-based System for The Stroke Survivor Feature Needs: A Qualitative Analysis View