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

Biomedical Engineering Reviews (12)

Published on in Vol 4, No 1 (2019): Jan-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/13732, first published .
Factors That Contribute to the Use of Stroke Self-Rehabilitation Technologies: A Review

Factors That Contribute to the Use of Stroke Self-Rehabilitation Technologies: A Review

Factors That Contribute to the Use of Stroke Self-Rehabilitation Technologies: A Review

Authors of this article:

Ioannis Vourganas1 Author Orcid Image ;   Vladimir Stankovic1 Author Orcid Image ;   Lina Stankovic1 Author Orcid Image ;   Andrew Kerr2 Author Orcid Image
Article Authors Cited by (19) Tweetations (2) Metrics

Journals

  1. Vourganas I, Stankovic V, Stankovic L, Michala A. Evaluation of Home-Based Rehabilitation Sensing Systems with Respect to Standardised Clinical Tests. Sensors 2019;20(1):26 View
  2. Dunne S, Close H, Richards N, Ellison A, Lane A. Maximizing Telerehabilitation for Patients With Visual Loss After Stroke: Interview and Focus Group Study With Stroke Survivors, Carers, and Occupational Therapists. Journal of Medical Internet Research 2020;22(10):e19604 View
  3. Vourganas I, Stankovic V, Stankovic L. Individualised Responsible Artificial Intelligence for Home-Based Rehabilitation. Sensors 2020;21(1):2 View
  4. Tsai M, Atputharaj S, Zariffa J, Wang R. Perspectives and expectations of stroke survivors using egocentric cameras for monitoring hand function at home: a mixed methods study. Disability and Rehabilitation: Assistive Technology 2024;19(3):878 View
  5. Gaboury I, Dostie R, Corriveau H, Demoustier A, Tousignant M. Use of a Telerehabilitation Platform in a Stroke Continuum: A Qualitative Study of Patient and Therapist Acceptability. International Journal of Telerehabilitation 2022;14(2) View
  6. Epalte K, Grjadovojs A, Bērziņa G. Use of the Digital Assistant Vigo in the Home Environment for Stroke Recovery: Focus Group Discussion With Specialists Working in Neurorehabilitation. JMIR Rehabilitation and Assistive Technologies 2023;10:e44285 View
  7. Knutson J, Fu M, Cunningham D, Hisel T, Friedl A, Gunzler D, Plow E, Busch R, Pundik S. Contralaterally controlled functional electrical stimulation video game therapy for hand rehabilitation after stroke: a randomized controlled trial. Disability and Rehabilitation 2024;46(19):4466 View
  8. Xuan Chua M, Okubo Y, Peng S, Nho Do T, Hui Wang C, Wu L. Analysis of Fatigue-Induced Compensatory Movements in Bicep Curls: Gaining Insights for the Deployment of Wearable Sensors. IEEE Transactions on Medical Robotics and Bionics 2024;6(3):1147 View
  9. Putra K, Suyasa I, Kamaryati N, Dharmapatni N. Development of a self-care guideline to prevent rehospitalization in stroke patients: a modified Delphi study. Jurnal Ners 2024;19(1):21 View
  10. Sánchez-Gil J, Sáez-Manzano A, López-Luque R, Ochoa-Sepúlveda J, Cañete-Carmona E. Gamified devices for stroke rehabilitation: A systematic review. Computer Methods and Programs in Biomedicine 2025;258:108476 View
  11. Román-Belmonte J, Corte-Rodríguez H, Rodríguez-Merchán E. Artificial intelligence in musculoskeletal conditions. Frontiers in Bioscience-Landmark 2021;26(11) View

Books/Policy Documents

  1. Michala A, Attar H, Vourganas I. Intelligent Healthcare. View
  2. Vourganas I, Attar H, Michala A. Intelligent Healthcare. View
  3. Attar H. Intelligent Healthcare. View
  4. Manuel Román-Belmonte J, De la Corte-Rodríguez H, Adriana Rodríguez-Damiani B, Carlos Rodríguez-Merchán E. Artificial Intelligence in Medicine and Surgery - An Exploration of Current Trends, Potential Opportunities, and Evolving Threats - Volume 1. View
  5. Saha S. Rehabilitation Robots for Neurorehabilitation in High-, Low-, and Middle-Income Countries. View
  6. Abdulaziz R, Loqman M. Recent Trends and Advances in Artificial Intelligence. View