Literature DB >> 19163023

Quantifying drug induced dyskinesia in Parkinson's disease patients using standardized videos.

Anusha S Rao1, Robert E Bodenheimer, Thomas L Davis, Rui Li, Cissy Voight, Benoit M Dawant.   

Abstract

This paper presents a video based method to quantify drug induced dyskinesias in Parkinson's disease (PD) patients. Dyskinetic movement in standard clinical videos of patients is analyzed by tracking landmark points on the video frames using non-rigid image registration. The novel application of Point Distribution Models (PDM) allows geometric variations and covariations of the landmark points to be captured from each video sequence. The PDM parameters represent quantifiable information that can be used to rate dyskinesia effectively, analogously to a neurologist's strategy of assessing the movement of multiple body parts simultaneously to effectively rate dyskinesia. A heuristic decision function is then developed using the PDM parameters to quantify the severity of the dyskinesia. The severity score using our decision function showed a high correlation to the dyskinesia rating of a neurologist on the corresponding patient videos.

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Year:  2008        PMID: 19163023     DOI: 10.1109/IEMBS.2008.4649520

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  2 in total

1.  Validating an objective video-based dyskinesia severity score in Parkinson's disease patients.

Authors:  Anusha Sathyanarayanan Rao; Benoit M Dawant; Robert E Bodenheimer; Rui Li; John Fang; Fenna Phibbs; Peter Hedera; Thomas Davis
Journal:  Parkinsonism Relat Disord       Date:  2012-11-20       Impact factor: 4.891

Review 2.  Co-evolution of machine learning and digital technologies to improve monitoring of Parkinson's disease motor symptoms.

Authors:  Anirudha S Chandrabhatla; I Jonathan Pomeraniec; Alexander Ksendzovsky
Journal:  NPJ Digit Med       Date:  2022-03-18
  2 in total

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