Airway - Modeling Laryngoscopy Simulation Device

Sponsor

Carle Illinois College of Medicine: Lidija Barbaric, Aaron Brown

Student Team

Master of Engineering: Yahia Rashed
Undergraduates: Dhruvi Kalariya, Taylor Wills, Hannah Laverty, Kristin Lai
iMBA: Paul Weyker, MD

Description

There are very few if any endotracheal intubation simulators that provide quantifiable insight into procedural accuracy or the mechanics of a successful intubation. This is a procedure that with much experience working with various anatomical variants, becomes second-nature to most providers. Eventually, after multiple failed attempts and years of struggle, calling in more senior members or utilization of video-guided laryngoscopy, the provider comes to intuit the difficulty of intubation, the correct approach and appropriate back-up plans to airway management. There are some patients for whom intubation will always require the aid of video laryngoscopy. However, for many novices, anatomically accessible airways are nevertheless a challenge to master due to inexperience. We propose a new approach to mastering airway management that suggests adjustments based on data gained from motion tracking devices that use machine-learning to assess diverse intubating situations.

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