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    Distinguishing Progressive Supranuclear Palsy from Parkinson’s Disease patients using gait analysis

    DIETI Contact person / Partner: Maria Romano

    Abstract

    The project consists in developing an innovative ICT platform which employs gait analysis parameters for supporting neurologist in managing patients affected by the so-called Movements Disorders. Gait analysis, a 3D, non-invasive and computerized exam, allows clinician to obtain a quantitative evaluation of gait; researchers have proved how these parameters could be useful to support neurologists combined with machine learning. Of note, recently, wearable sensors and m-health apps have been employed to perform gait analysis and distinguish two forms of Parkinson’s Disease.

    Objective

    Design and development of an experimental system which uses as input the spatial and temporal parameters of gait analysis and employs machine learning techniques to provide neurologists with a clinical decision support system.

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    Available

    Can be assigned to one doctoral student of cycle XXXVII 

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