medRxiv PreprintsInternational13 November 2026
DxToniaNet: A Neural Network for Estimating the Severity of Leg Dystonia in Children with Cerebral Palsy
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Importance: Leg dystonia affects 50-80% of children with cerebral palsy (CP), but severity assessment remains subjective and time-consuming. Objective tools are urgently needed to quantify leg dystonia severity in clinical care and clinical trials. Objective: To develop and validate a deep neural network (DxToniaNet) for leg dystonia severity estimation using 2D clinical video recordings. Design, Setting, and Participants: We retrospectively analyzed video recordings of 298 children with cerebral palsy undergoing a seated hand open-close task as part of routine clinical care (Center 1: 193 vid
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