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

Cognitive and Neurorehabilitation (349)

Published on in Vol 5, No 2 (2018): Jul-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/10714, first published .
Capturing Expert Knowledge for the Personalization of Cognitive Rehabilitation: Study Combining Computational Modeling and a Participatory Design Strategy

Capturing Expert Knowledge for the Personalization of Cognitive Rehabilitation: Study Combining Computational Modeling and a Participatory Design Strategy

Capturing Expert Knowledge for the Personalization of Cognitive Rehabilitation: Study Combining Computational Modeling and a Participatory Design Strategy

Authors of this article:

Ana Lúcia Faria1, 2 Author Orcid Image ;   Maria Salomé Pinho2, 3 Author Orcid Image ;   Sergi Bermúdez i Badia1, 4 Author Orcid Image
Article Authors Cited by (13) Tweetations (2) Metrics

Journals

  1. Faria A, Pinho M, Bermúdez i Badia S. A comparison of two personalization and adaptive cognitive rehabilitation approaches: a randomized controlled trial with chronic stroke patients. Journal of NeuroEngineering and Rehabilitation 2020;17(1) View
  2. Garcia-Rudolph A, Opisso E, Tormos J, Madai V, Frey D, Becerra H, Kelleher J, Bernabeu Guitart M, López J. Toward Personalized Web-Based Cognitive Rehabilitation for Patients With Ischemic Stroke: Elo Rating Approach. JMIR Medical Informatics 2021;9(11):e28090 View
  3. Câmara J, Ferreira R, Teixeira L, Nóbrega J, Romeira C, Badia S, Faria A. Efficacy of adaptive cognitive training through desktop virtual reality and paper-and-pencil in the treatment of mental and behavioral disorders. Virtual Reality 2023;27(1):291 View
  4. Faria A, Almeida Y, Branco D, Câmara J, Cameirão M, Ferreira L, Moreira A, Paulino T, Rodrigues P, Spinola M, Vilar M, Bermúdez i Badia S, Simões M, Fermé E. NeuroAIreh@b: an artificial intelligence-based methodology for personalized and adaptive neurorehabilitation. Frontiers in Neurology 2024;14 View
  5. Fan Y, Zhu L, Wang H, Song A. Synthesize Personalized Training for Robot-Assisted Upper Limb Rehabilitation With Diversity Enhancement. IEEE Transactions on Visualization and Computer Graphics 2024;30(8):5705 View
  6. Zhou J, Salvendy G, Boot W, Charness N, Czaja S, Gao Q, Holzinger A, Ntoa S, Rau P, Rogers W, Stephanidis C, Wahl H, Ziefle M. Grand Challenges of Smart Technology for Older Adults. International Journal of Human–Computer Interaction 2025:1 View
  7. Marcos T, Faria A, i Badia S, Quintal F. Task Generator 2.0: Integrating Interactive Technology with Personalized Task Generation. Procedia Computer Science 2025;256:1285 View
  8. Costa R, Lima S, S․ Cameirão M, Badia S, Faria A. Enhancing treatment outcomes of Alcohol Use Disorder patients through ICT-based cognitive training tools: a randomized controlled trial. International Journal of Clinical and Health Psychology 2025;25(3):100623 View
  9. Li W, Gao W, Lin X. Virtual Reality-Based Cognitive and Physical Interventions in Cognitive Impairment: A Network Meta-Analysis of Immersion Level Effects. Behavioral Sciences 2025;15(12):1610 View

Books/Policy Documents

  1. Muñoz J, Montoya M, Boger J. Smart Home Technologies and Services for Geriatric Rehabilitation. View

Conference Proceedings

  1. Paulino T, Faria A, Bermudez i Badia S. 2019 5th Experiment International Conference (exp.at'19). Reh@City v2.0: a comprehensive virtual reality cognitive training system based on personalized and adaptive simulations of activities of daily living View
  2. Faria A, Paulino T, Badia S. 2019 International Conference on Virtual Rehabilitation (ICVR). Comparing adaptive cognitive training in virtual reality and paper-pencil in a sample of stroke patients View
  3. Fan Y, Zhu L, Wang H, Song A. 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW). Individualized Generation of Upper Limb Training for Robot-assisted Rehabilitation using Multi-objective Optimization View