Beyond the Scope: Using Motion Capture Data from Bronchoscopy Simulations to Build Feedback Models
Author(s)
Babichenko, Dmitriy
Grieve, Lorin
Velez, Jonathan
Lutz, John
Farkas, Deborah
Bailey, Kailani
Freeman, Morgan
Wynn, Taylor
Issue Date
2018
Keyword(s)
Bronchoscopy
Simulation
Motion capture
Feedback modeling
Abstract
Mannequin simulators and task trainers are commonly used in health sciences training programs to teach techniques performed during medical procedures. However, there are drawbacks to their deployment. First and foremost, the cost of high-fidelity task trainers is prohibitively expensive for many programs. Additionally, the combination of mannequin-to-learner and teacher-to-learner ratios often makes it difficult to efficiently teach procedures to a large number of students. This project aims to create a low-cost, game-based, easily portable task trainer to assist learners in building skills and expertise in performing bronchoscopies. This preliminary report focuses on designing a motion capture device to record hand, wrist, and thumb motions performed by experts and learners during simulated bronchoscopy procedures and then using this captured data to construct computational feedback models.
Publisher
iSchools
Series/Report Name or Number
iConference 2018 Proceedings
Type of Resource
text
Language
eng
Permalink
http://hdl.handle.net/2142/100270
Copyright and License Information
Copyright 2018 is held by Dmitry Babichenko, Lorin Grieve, Jonathan Velez, John Lutz, Deborah Farkas, Kailani Bailey, Morgan Freeman, Taylor Wynn. Copyright permissions, when appropriate, must be obtained directly from the authors.
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