Designing an active motor skill learning platform with a robot-assisted laparoscopic trainer

Chun Siong Lee, Liangjing Yang, Tao Yang, Chee Kong Chui, Jiang Liu, Weimin Huang, Yi Su, Stephen K.Y. Chang

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

4 Citations (Scopus)

Abstract

Laparoscopic Surgery poses significant complexity in hand-eye coordination to the surgeon. In order to improve their proficiency beyond the limited exposure in the operating theatre, surgeons need to practice on laparoscopic trainers. We have constructed a robotic laparoscopic trainer with identical degrees of freedom and range of motion as a conventional laparoscopic instrument. We hypothesize that active robotic assistance through a laparoscopic trainer improves training efficacy as compared to autonomous practice. In order to test the hypothesis, we have divided the subjects into two groups. The control group practiced on two laparoscopic tasks manually without feedback or supervision. The other group practiced on the same tasks with robotic assistance. Results from the robot-assisted group show that tool orientation (pitch and yaw joint motion) in the pointing task improved by more than 15%.

Original languageEnglish
Title of host publication33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Pages4534-4537
Number of pages4
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 - Boston, MA, United States
Duration: 30 Aug 20113 Sep 2011

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
ISSN (Print)1557-170X

Conference

Conference33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011
Country/TerritoryUnited States
CityBoston, MA
Period30/08/113/09/11

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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