Using deep learning to detect upper limb compensation in individuals post-stroke using consumer-grade webcams-A feasibility study.
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| Title: | Using deep learning to detect upper limb compensation in individuals post-stroke using consumer-grade webcams-A feasibility study. |
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| Authors: | Unger T; Data Analytics and Rehabilitation Technology (DART), Lake Lucerne Institute, Vitznau, Switzerland., Kühnis B; ZHAW School of Management and Law, Institute of Business Information Technology, Winterthur, Switzerland., Sauerzopf L; ZHAW School of Health Sciences, Institute of Occupational Therapy, Winterthur, Switzerland.; Faculty of Medicine, University of Zurich, Zurich, Switzerland., Spiess MR; ZHAW School of Health Sciences, Institute of Occupational Therapy, Winterthur, Switzerland.; Faculty of Medicine, University of Zurich, Zurich, Switzerland., de Spindler A; ZHAW School of Management and Law, Institute of Business Information Technology, Winterthur, Switzerland., Luft AR; Division of Vascular Neurology and Neurorehabilitation, Department of Neurology and Clinical Neuroscience Center, University of Zurich and University Hospital Zurich, Zurich, Switzerland.; Cereneo, Center for Neurology and Rehabilitation, Vitznau, Switzerland.; Neurocore Lab, Lake Lucerne Institute, Vitznau, Switzerland., Easthope Awai C; Data Analytics and Rehabilitation Technology (DART), Lake Lucerne Institute, Vitznau, Switzerland., Schönhammer JG; Division of Vascular Neurology and Neurorehabilitation, Department of Neurology and Clinical Neuroscience Center, University of Zurich and University Hospital Zurich, Zurich, Switzerland.; Neurocore Lab, Lake Lucerne Institute, Vitznau, Switzerland., Gavagnin E; ZHAW School of Management and Law, Institute of Business Information Technology, Winterthur, Switzerland.; ZHAW School of Engineering, Centre for Artificial Intelligence, Winterthur, Switzerland. |
| Source: | Frontiers in medicine [Front Med (Lausanne)] 2025 Nov 14; Vol. 12, pp. 1645369. Date of Electronic Publication: 2025 Nov 14 (Print Publication: 2025). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Frontiers Media S.A Country of Publication: Switzerland NLM ID: 101648047 Publication Model: eCollection Cited Medium: Print ISSN: 2296-858X (Print) Linking ISSN: 2296858X NLM ISO Abbreviation: Front Med (Lausanne) Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 2296-858X |
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| DOI: | 10.3389/fmed.2025.1645369 |
