Computer Aided Identification of Motion Disturbances Related to Parkinson’s Disease

Gudmundur Einarsson, Line Katrine Harder Clemmensen, Ditte Rudå, Anders Fink-Jensen, Jannik Nielsen, Anne Pagsberg, Kristian Winge, Rasmus Reinhold Paulsen

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

We present a framework for assessing which types of simple movement tasks are most discriminative between healthy controls and Parkinson’s patients. We collected movement data in a game-like environment, where we used the Microsoft Kinect sensor for tracking the user’s joints. We recruited 63 individuals for the study, of whom 30 had been diagnosed with Parkinson’s disease. A physician evaluated all participants on movement-related rating scales, e.g., elbow rigidity. The participants also completed the game task, moving their arms through a specific pattern. We present an innovative approach for data acquisition in a game-like environment, and we propose a novel method, sparse ordinal regression, for predicting the severity of motion disorders from the data.
Original languageEnglish
Title of host publicationInternational Workshop on PRedictive Intelligence In MEdicine
Number of pages8
PublisherSpringer
Publication date2018
Pages1-8
ISBN (Print)978-3-030-00319-7
DOIs
Publication statusPublished - 2018
EventInternational Workshop on PRedictive Intelligence In MEdicine - Granada, Spain
Duration: 16 Sep 201816 Sep 2018

Conference

ConferenceInternational Workshop on PRedictive Intelligence In MEdicine
CountrySpain
CityGranada
Period16/09/201816/09/2018
SeriesLecture Notes in Computer Science
Volume11121
ISSN0302-9743

Keywords

  • Game-aided diagnosis
  • Kinect
  • Parkinson’s disease
  • Sparse
  • Ordinal
  • Classification

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