A quality of performance model for evaluating post-stroke patients

Atif Alamri, Mohamad Eid, Abdulmotaleb El Saddik

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Augmented Reality (AR) has recently emerged as an assistive tool for effective diagnosis and rehabilitation intervention. However, measuring the Quality of Performance (QoP) of patients has gained limited attention from the research community. The objective of this paper is to propose and test a evaluation taxonomy for an AR-based stroke patient rehabilitation system that is currently under development at the MCRlab, University of Ottawa. The taxonomy is modeled using a Fuzzy Logic Inference (FLI) system to quantitatively measure the QoP of the patient and eventually provide the therapist with discrete recommendation regarding the progress of patient treatment.

Original languageEnglish (US)
Title of host publicationCIMSA 2008 - IEEE Conference on Computational Intelligence for Measurement Systems and Applications Proceedings
Pages14-18
Number of pages5
DOIs
StatePublished - 2008
Event2008 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications, IEEE CIMSA 2008 - Istanbul, Turkey
Duration: Jul 14 2008Jul 16 2008

Publication series

NameCIMSA 2008 - IEEE Conference on Computational Intelligence for Measurement Systems and Applications Proceedings

Other

Other2008 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications, IEEE CIMSA 2008
CountryTurkey
CityIstanbul
Period7/14/087/16/08

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Control and Systems Engineering

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