Automated assessment of levodopa-induced dyskinesia: Evaluating the responsiveness of video-based features.

Journal: Parkinsonism & related disorders
Published Date: Aug 1, 2018

Abstract

INTRODUCTION: Technological solutions for quantifying Parkinson's disease (PD) symptoms may provide an objective means to track response to treatment, including side effects such as levodopa-induced dyskinesia. Vision-based systems are advantageous as they do not require physical contact with the body and have minimal instrumentation compared to wearables. We have developed a vision-based system to quantify a change in dyskinesia as reported by patients using 2D videos of clinical assessments during acute levodopa infusions.

Authors

  • Michael H Li
    Toronto Rehabilitation Institute, University Health Network, 550 University Ave, Toronto, Ontario, M5G 2A2, Canada; Institute of Biomaterials and Biomedical Engineering, University of Toronto, 164 College St, Room 407, Toronto, Ontario, M5S 3G9, Canada. Electronic address: michaelhg.li@alum.utoronto.ca.
  • Tiago A Mestre
    Edmond J. Safra Program in Parkinson's Disease, Toronto Western Hospital, University Health Network, 399 Bathurst St, Toronto, Ontario, M5T 2S8, Canada; The Ottawa Hospital Research Institute, 1053 Carling Ave, Ottawa, Ontario, K1Y 4E9, Canada; Division of Neurology, Department of Medicine, 1053 Carling Ave, Ottawa, Ontario, K1Y 4E9, Canada; Division of Neurology, University of Toronto, Suite RFE 3-805, 200 Elizabeth St, Toronto, Ontario, M5G 2C4, Canada. Electronic address: tmestre@toh.ca.
  • Susan H Fox
    Edmond J. Safra Program in Parkinson's Disease, Toronto Western Hospital, University Health Network, 399 Bathurst St, Toronto, Ontario, M5T 2S8, Canada; Division of Neurology, University of Toronto, Suite RFE 3-805, 200 Elizabeth St, Toronto, Ontario, M5G 2C4, Canada. Electronic address: susan.fox@uhnresearch.ca.
  • Babak Taati

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