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Sabatino, Etty; Moschetta, Miriam; Lucaroni, Andrea; Barresi, Giacinto; Ferraresi, Carlo; Podda, Jessica; Grange, Erica; Brichetto, Giampaolo and Bucchieri, Anna
(2025).
DOI: https://doi.org/10.3390/virtualworlds4010004
Abstract
The assessment and rehabilitation of upper-limb functionality are crucial for addressing motor disorders in individuals with multiple sclerosis (PwMS). Traditional methods often lack the sensitivity to quantify subtle motor impairments, with cerebellar tremor diagnosis typically based on subjective visual inspections by clinicians. This study explored the feasibility of using Microsoft HoloLens2 for motion capture to assess upper-limb function in PwMS. Using the ROCKapp application, kinematic metrics such as movement quality and oculomotor coordination were recorded during pick-and-place tasks. Data from twelve healthy individuals served as benchmarks, while nine PwMS, including three with cerebellar tremor and one with ataxia, were tested to evaluate the tool’s diagnostic potential. Clustering algorithms applied to the kinematic data classified participants into distinct groups, showing that PwMS without cerebellar symptoms sometimes displayed behavior similar to healthy controls. However, those with cerebellar conditions, like tremor and ataxia, were more easily differentiated. While the HoloLens2 shows promise in detecting motor impairments, further refinement is required to improve sensitivity for those without overt cerebellar symptoms. Despite these challenges, this approach offers potential for personalized rehabilitation, providing detailed feedback that could improve interventions and enhance quality of life for PwMS. In conclusion, these findings highlight the potential of mixed-reality tools to refine diagnostic accuracy, suggesting future studies to validate their integration in clinical rehabilitation programs.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)
