Fuzzy logic-based performance assessment in the Virtual, Assistive Surgical Trainer (VAST)

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

8 Scopus citations

Abstract

The Virtual Assistive Surgical Trainer (VAST) is an approach developed to train surgeons in minimally invasive procedures. It uses surgical instruments augmented with micro-sensors, and knowledge-based inference techniques to provide objective, data-driven feedback and performance assessment for complex exercises. The assessment is typically based on the expertise of senior surgeons and, thus, a single objective standard is difficult to define. To formulate such a standard, and to provide an accurate scoring method, a fuzzy logic method is proposed in this paper. This makes it easier to mimic tasks that are already successfully performed by human experts. A multi-level fuzzy inference engine and new performance metrics are implemented. Experimental results demonstrate the feasibility of this method and the efficacy of the new performance metrics.

Original languageEnglish (US)
Title of host publicationProceedings - Fifteenth IEEE International Conference and Workshops on the Engineering of Computer-Based Systems, ECBS 2008
Pages203-209
Number of pages7
DOIs
StatePublished - 2008
Event15th IEEE International Conference and Workshops on the Engineering of Computer-Based Systems, ECBS 2008 - Belfast, United Kingdom
Duration: Mar 31 2008Apr 4 2008

Publication series

NameProceedings - Fifteenth IEEE International Conference and Workshops on the Engineering of Computer-Based Systems, ECBS 2008

Other

Other15th IEEE International Conference and Workshops on the Engineering of Computer-Based Systems, ECBS 2008
Country/TerritoryUnited Kingdom
CityBelfast
Period3/31/084/4/08

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Control and Systems Engineering
  • Theoretical Computer Science
  • Hardware and Architecture

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