An optimized haptic interaction model based on support vector regression for evaluation of endodontic shaping skill

Min Li*, Yun Hui Liu, Qiang Huang

*Corresponding author for this work

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

3 Citations (Scopus)

Abstract

Effective and objective evaluation of endodontic skill is crucial to the interactive simulation of this operation. In this paper, we present a novel evaluation method based on an optimized haptic interaction model characterizing endodontic shaping by applying new statistical learning techniques to this problem. We first present a novel robotic measurement system to collect detailed haptic data during real endodontic shaping operations conducted by experts and establish the needed haptic training set. Then we propose a support vector regression model to estimate the haptic interaction for endodontic shaping. The regression model uses RBF kernel for training, and the optimized parameters of the learned model are obtained by experiments. Applying this model to the virtual endodontic training system, we can evaluate the shaping operations conducted in the virtual environment convincingly.

Original languageEnglish
Title of host publication2007 IEEE International Conference on Robotics and Biomimetics, ROBIO
PublisherIEEE Computer Society
Pages617-622
Number of pages6
ISBN (Print)9781424417582
DOIs
Publication statusPublished - 2007
Event2007 IEEE International Conference on Robotics and Biomimetics, ROBIO - Yalong Bay, Sanya, China
Duration: 15 Dec 200718 Dec 2007

Publication series

Name2007 IEEE International Conference on Robotics and Biomimetics, ROBIO

Conference

Conference2007 IEEE International Conference on Robotics and Biomimetics, ROBIO
Country/TerritoryChina
CityYalong Bay, Sanya
Period15/12/0718/12/07

Keywords

  • Endodontic skill evaluation
  • Haptic model
  • Support vector regression

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