AI-based 3D Anthropometric Modeling for Automated Assessment of Dystonia Patients (P10-5.002)
Our primary objective is to formulate and test an AI algorithm that can accurately assess the severity of dystonia. Secondarily we want to collect data on the kinematic properties of patients with dystonia, classifying patient movements into characteristics such as joint angles and velocities.
Authors
- S. Mandal (ORCID: https://orcid.org/0000-0002-8397-6206)
- Kanad Dev Nayar (ORCID: https://orcid.org/0000-0002-2166-9606)
- Divya Nayar (ORCID: https://orcid.org/0000-0002-0711-9720)
Institutions
- Massachusetts General Hospital (US)
- University of Arkansas for Medical Sciences (US)
Publication Details
- Journal
- Neurology
- Published
- 2025-04-07
- DOI
- https://doi.org/10.1212/wnl.0000000000212190
- Primary Topic
- Stroke Rehabilitation and Recovery
- Type
- article
- Field-Weighted Citation Impact
- 0.00