Multivideo Models for Classifying Hand Impairment After Stroke Using Egocentric Video
The proposed deep learning solution is the first of its kind in multi-video analysis, and opens the door to further applications in automating other multi-observation assessments for clinical use.
Authors
- José Zariffa (ORCID: https://orcid.org/0000-0002-8842-745X)
- Meng-Fen Tsai (ORCID: https://orcid.org/0000-0002-4594-7463)
- Anne Mei (ORCID: https://orcid.org/0009-0000-9743-8065)
Institutions
- University Health Network (CA)
- University of Toronto (CA)
- Toronto Rehabilitation Institute (CA)
Publication Details
- Journal
- IEEE Transactions on Neural Systems and Rehabilitation Engineering
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/tnsre.2025.3596488
- Citations
- 1
- Primary Topic
- Stroke Rehabilitation and Recovery
- Type
- article
- Field-Weighted Citation Impact
- 1.03
Funders
- Heart and Stroke Foundation of Canada
- Natural Sciences and Engineering Research Council of Canada