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Title: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
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.
Issue Date:2018
Series/Report:iConference 2018 Proceedings
Genre:Conference Poster
Rights 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.
Date Available in IDEALS:2018-07-12

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