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Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
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QAPD: an integrated system to quantify symptoms of Parkinson's disease

Vrajeshri Patel, Martin Burns, Michael Pourfar

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |March 9, 2017
    PubMed

    Abstract:

    The complex prevalence of Parkinson's disease (PD) symptoms has pushed research towards assessment tools that can assist in their quantification. There remains a need for a system capable of measuring symptoms during various tasks at multiple motor levels (kinematics and electromyography). In this paper, we present the development and initial validation of a quantitative assessment tool for Parkinson's disease (QAPD), a system designed to assist researchers and clinicians in the study of PD. The system integrates motion tracking, data gloves, and electromyography to collect movement related data from multiple body parts. As part of the system, a custom MATLAB® based toolbox has been designed to quantify bradykinesia, tremor, micrographia, and muscle rigidity using both standard and contemporary data analysis techniques. We believe this system can be a useful assessment tool to assist clinicians and researchers in diagnosing and estimating movement dysfunction in individuals with PD.

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