Recommendations for Combining Brain-Computer Interface, Motor Imagery, and Virtual Reality in Upper Limb Stroke Rehabilitation: Qualitative Participatory Design Study

Current results contribute to establishing clear guidelines on patient selection, task design, intervention structuring, motivation factors, and tailoring of sensory feedback. This framework presents a foundation for optimal implementation of VR-BCI-based interventions that associate MI and motor observation, optimizing cortical activity during the intervention, patients' engagement, and clinical outcomes. Future research should explore the application of these guidelines for validation and investigate BCIs' efficacy according to different combinations of patients' profiles, task characteristics, and technology features.

Authors

Institutions

Publication Details

Journal
JMIR Rehabilitation and Assistive Technologies
Published
2025-10-15
DOI
https://doi.org/10.2196/71789
Citations
1
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
1.43
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Recommendations for Combining Brain-Computer Interface, Motor Imagery, and Virtual Reality in Upper Limb Stroke Rehabilitation: Qualitative Participatory Design Study

Ana Paula Ribeiro de Almeida, Miguel Russo, Athanasios Vourvopoulos, Isabela Ferreira de Oliveira et al.
1 citations
JMIR Rehabilitation and Assistive Technologies
EEG and Brain-Computer Interfaces
1.43
article

Recommendations for Combining Brain-Computer Interface, Motor Imagery, and Virtual Reality in Upper Limb Stroke Rehabilitation: Qualitative Participatory Design Study

Ana Paula Ribeiro de Almeida, Miguel Russo, Athanasios Vourvopoulos, Isabela Ferreira de Oliveira, Carla Mendes Pereira
article en
1 citations

Abstract

Current results contribute to establishing clear guidelines on patient selection, task design, intervention structuring, motivation factors, and tailoring of sensory feedback. This framework presents a foundation for optimal implementation of VR-BCI-based interventions that associate MI and motor observation, optimizing cortical activity during the intervention, patients' engagement, and clinical outcomes. Future research should explore the application of these guidelines for validation and investigate BCIs' efficacy according to different combinations of patients' profiles, task characteristics, and technology features.

JMIR Rehabilitation and Assistive TechnologiesVol. 12
Universidade Politécnica de Lisboa (PT), Universidade Politécnica de Setúbal (PT), Centro de Medicina de Reabilitacao do Alcoitão (PT), Centre for Research in Anthropology (PT), Escola Superior de Saúde do Alcoitão (PT), Institute for Biotechnology and Bioengineering (PT), Universidade Nova de Lisboa (PT)
Openalex Percentile: Top 15%
EEG and Brain-Computer Interfaces
1.43
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Recommendations for Combining Brain-Computer Interface, Motor Imagery, and Virtual Reality in Upper Limb Stroke Rehabilitation: Qualitative Participatory Design Study — Ana Paula Ribeiro de Almeida, Miguel Russo, et al. · JMIR Rehabilitation and Assistive Technologies (2025) | TGRS Research Map | TGRS