Video summarization for home-based egocentric footage in spinal cord injury rehabilitation
All three algorithms produced adequate video summaries that captured essential content. However, enhancing the depiction of aspects such as functional difficulties and compensatory strategies could further improve the clinical value of the summaries. Moreover, discrepancies between computational and manual evaluations highlight the need to train algorithms on more human-centered criteria. Overall, this work demonstrates the potential of automatic video summarization to support the integration of wearable cameras into outpatient SCI rehabilitation.
Authors
- José Zariffa (ORCID: https://orcid.org/0000-0002-8842-745X)
- Catherine R. Jutzeler (ORCID: https://orcid.org/0000-0001-7167-8271)
- Melina Giagiozis
- Armin Curt
Institutions
- SIB Swiss Institute of Bioinformatics (CH)
- University of Toronto (CA)
- Toronto Rehabilitation Institute (CA)
- ETH Zurich (CH)
- Universitätsklinik Balgrist (CH)
Publication Details
- Journal
- BioMedical Engineering OnLine
- Published
- 2026-01-02
- DOI
- https://doi.org/10.1186/s12938-025-01506-1
- Primary Topic
- Human Pose and Action Recognition
- Type
- article
- Field-Weighted Citation Impact
- 0.00