A virtual training system for maxillofacial surgery using advanced haptic feedback and immersive workbench

Fule Wu, Xiaojun Chen, Yanping Lin, Chengtao Wang, Xudong Wang, Guofang Shen, Jing Qin, Pheng Ann Heng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

33 Citations (Scopus)


Background: VR-based surgery simulation provides a cost-effective and efficient method to train novices. In this study, a virtual training system for maxillofacial surgery (VR-MFS), which aims mainly at the simulation of operations on mandible and maxilla, was developed and demonstrated. Methods: The virtual models of the anatomic structures were reconstructed from CT data, and the virtual instruments were built from laser scanning data using reverse engineering technology. For collision detection, axis aligned bounding boxes (AABBs) were constructed for the anatomic models. Then, the simulation algorithms were developed, and the haptic force feedback was consequently calculated based on regression equations. Finally, the vivid 3D stereo effect was implemented with the use of an immersive workbench. Results: A virtual training system for maxillofacial surgery was developed; in particular, the application for Le-Fort I osteotomy was implemented. The tactile, visual and aural effects were highly integrated, making the virtual surgical environment vivid and realistic. Conclusions: The VR-MFS provides an effective approach in terms of helping novices to become familiar with maxillofacial surgery procedures. The same method can also be applied to other bone simulations.
Original languageEnglish
Pages (from-to)78-87
Number of pages10
JournalInternational Journal of Medical Robotics and Computer Assisted Surgery
Issue number1
Publication statusPublished - 1 Jan 2014
Externally publishedYes


  • Collision detection
  • Haptic feedback
  • Maxillofacial surgery
  • Surgery simulation
  • Virtual reality

ASJC Scopus subject areas

  • Surgery
  • Biophysics
  • Computer Science Applications


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