Transfer of Automated Performance Feedback Models to Different Specimens in Virtual Reality Temporal Bone Surgery

Jesslyn Lamtara, Nathan Hanegbi, Benjamin Talks, Sudanthi Wijewickrema, Xingjun Ma, Patorn Piromchai, James Bailey, Stephen O’Leary

International Conference on Artificial Intelligence in Education



Virtual reality has gained popularity as an effective training platform in many fields including surgery. However, it has been shown that the availability of a simulator alone is not sufficient to promote practice. Therefore, simulator-based surgical curricula need to be developed and integrated into existing surgical training programs. As practice variation is an important aspect of a surgical curriculum, surgical simulators should support practice on multiple specimens. Furthermore, to ensure that surgical skills are acquired, and to support self-guided learning, automated feedback on performance needs to be provided during practice. Automated feedback is typically provided by comparing real-time performance with expert models generated from pre-collected data. Since collecting data on multiple specimens for the purpose of developing feedback models is costly and time-consuming, methods of transferring feedback from one specimen to another should be investigated. In this paper, we discuss a simple method of feedback transfer between specimens in virtual reality temporal bone surgery and validate the accuracy and effectiveness of the transfer through a user study.