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Title page for ETD etd-03262012-214139


Type of Document Dissertation
Author Sathyanarayanan Rao, Anusha
Author's Email Address anusha.rao@vanderbilt.edu
URN etd-03262012-214139
Title Quantifying drug-induced dyskinesia using clinical videos of Parkinson’s disease patients
Degree PhD
Department Electrical Engineering
Advisory Committee
Advisor Name Title
Benoit Dawant Committee Chair
Robert Bodenheimer Committee Co-Chair
A. B. Bonds Committee Member
Mitchell Wilkes Committee Member
Thomas Davis Committee Member
Keywords
  • Severity Score
  • Dyskinesia
  • Parkinsons Disease
  • Rating Scales
Date of Defense 2012-02-23
Availability unrestricted
Abstract
Levodopa remains the most effective medication for Parkinson’s disease. Prolonged use of levodopa leads to a side effect called dyskinesia that is characterized by abnormal involuntary movements. The assessment of dyskinesia severity is essential to develop better therapies to treat it. Qualitative assessments using rating scales/questionnaires are rater-dependent and lack rating resolution. In this work, we propose a low-cost, patient-friendly, video-based technique that quantifies dyskinesia severity with a single score incorporating most of its attributes. This dissertation makes three main contributions to the field. The first contribution is the development of a severity score called SVS that is based on the covariance of points that were automatically tracked in video sequences using non-rigid image registration. The second contribution is the validation of SVS, which was done by comparing it to severity rankings by trained neurologists based on the clinical definition of dyskinesia. Results show a moderate but statistically significant correlation between automatic and manual rankings. The third contribution is a modified severity score that uses frequency dispersion parameters to differentiate between choreic and dystonic movement. Results show that adding these frequency dispersion parameters improves the correlation between manual and automatic scores.
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