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abstract

LocalAnesthesiaVR

Published:11 August 2021Publication History

ABSTRACT

LocalAnesthesiaVRis a virtual reality training system for dental anesthesia, a clinical procedure every dentist must be competent with, and one that is particularly challenging to master throughout the demanding dental curriculum. This unique VR-based system provides learners with visual, auditory and haptic feedback enabling experiential learning in pre-clinical education.

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References

  1. Mina C. Johnson-Glenberg. 2018. Immersive VR and Education: Embodied Design Principles That Include Gesture and Hand Controls. https://doi.org/10.3389/frobt.2018.00081Google ScholarGoogle Scholar
  2. Andrew L Kary, Juliana Gomez, Samuel D. Raffaelli, and Marci H. Levine. 2018. Preclinical Local Anesthesia Education in Dental Schools: A Systematic Review. pubmed.ncbi.nlm.nih.gov/30275140Google ScholarGoogle Scholar
  3. Adam I. Levine, Samuel DeMaria Jr., Andrew D. Schwartz, and Alan J. Sim. 2013. The Comprehensive Textbook of Healthcare Simulation. google.com/books/edition/The_Comprehensive_Textbook_of_Healthcare/WWRDAAAAQBAJ?hl=enGoogle ScholarGoogle Scholar

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  1. LocalAnesthesiaVR
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        • Published in

          cover image ACM Conferences
          SIGGRAPH '21: ACM SIGGRAPH 2021 Educators Forum
          August 2021
          265 pages
          ISBN:9781450383639
          DOI:10.1145/3450549

          Copyright © 2021 Owner/Author

          Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 11 August 2021

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          • Refereed limited

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          Overall Acceptance Rate1,822of8,601submissions,21%
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