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Innovations

Vol. 2 No. 1 (2026)

Utilizing a Voice-Guided Mixed Reality and Artificial Intelligence based platform for Difficult Intubation Simulation in Austere Teaching Environments

Submitted
26 November 2025
Published
09-04-2026

Abstract

Background: Intubating a blood-contaminated airway is a high acuity, low occurrence procedure.  In resource-limited environments, a high-fidelity bloody airway simulation is restricted by cost, equipment, and a lack of expert feedback. To bridge this gap, we developed a high-fidelity artificial intelligence (AI) and augmented reality (AR) informed simulation tool. Inside an AR headset, an overlay is generated over a standard airway manikin. The user then proceeds through a bloody airway scenario with integrated instructional feedback videos.

Methods: We utilized a Unity AR application integrated into an AR Headset that interacts with a laryngoscope and removable pressure, light, and proximity sensors inside a manikin. The sensors and laryngoscope are connected to a Raspberry Pi that transmits sensor and video data via WebSocket to the headset. The headset application also processes audio via Meta’s Wit.AI service for transcription and intent recognition. The application handles simulation logic, sensor / video data handling, and the AR guidance display. A decision tree algorithm enables user interaction and feedback.

Results: Both non-medical users at the 2024 DALI exhibition and individuals with emergency medicine backgrounds at the 2025 Society for Academic Emergency Medicine Innovation exhibit reported that the device was educational for difficult airway management. However, challenges have arisen in terms of stable connectivity with the Raspberry Pi under certain internet network conditions. 

Conclusions: Utilizing readily available AI and AR technologies, a simulation device can be developed to teach difficult airway management in resource-limited areas, providing both experience and constructive feedback from experts.

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