Classification and clustering of brain injuries from motion data of patients in a virtual reality environment

Uri Feintuch, Larry Manevitz, Natan Silnitsky

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Virtual Reality (VR) has been found to be an effective rehabilitation tool for brain injury patients. We show that motion data from these VR sessions can be effectively used to both cluster and classify patients according to types of injury. Neural Network and other tools were used to differentially classify patients with traumatic brain injury, cerebral vascular accident (stroke) with and without spatial neglect and healthy individuals solely from the motion data. Clustering techniques also successfully duplicated the classification division. These results have potential implications for scientific research, automated diagnosis and integrated individually adaptive therapies in the virtual reality technology.

Original languageEnglish
Title of host publicationICFC 2010 ICNC 2010 - Proceedings of the International Conference on Fuzzy Computation and International Conference on Neural Computation
Pages246-252
Number of pages7
StatePublished - 2010
EventInternational Conference on Neural Computation, ICNC 2010 and of the International Conference on Fuzzy Computation, ICFC 2010 - Valencia, Spain
Duration: 24 Oct 201026 Oct 2010

Publication series

NameICFC 2010 ICNC 2010 - Proceedings of the International Conference on Fuzzy Computation and International Conference on Neural Computation

Conference

ConferenceInternational Conference on Neural Computation, ICNC 2010 and of the International Conference on Fuzzy Computation, ICFC 2010
Country/TerritorySpain
CityValencia
Period24/10/1026/10/10

Keywords

  • CVA
  • Classification
  • Clustering
  • Neglect
  • Neural networks
  • TBI
  • VR

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Applied Mathematics

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