| Literature DB >> 35515734 |
Thomas J Caruso1, Olivia Hess1, Kenny Roy2, Ellen Wang1, Samuel Rodriguez1, Coby Palivathukal3, Nick Haber4.
Abstract
Augmented reality (AR) has been studied as a clinical teaching tool, however eye-tracking capabilities integrated within an AR medical simulator have limited research. The recently developed Chariot Augmented Reality Medical (CHARM) simulator integrates real-time communication into a portable medical simulator. The purpose of this project was to refine the gaze-tracking capabilities of the CHARM simulator on the Magic Leap One (ML1). Adults aged 18 years and older were recruited using convenience sampling. Participants were provided with an ML1 headset that projected a hologram of a patient, bed and monitor. They were instructed via audio recording to gaze at variables in this scenario. The participant gaze targets from the ML1 output were compared with the specified gaze points from the audio recording. A priori investigators planned to iterative modifications of the eye-tracking software until a capture rate of 80% was achieved. Two consecutive participants with a capture rate less than 80% triggered software modifications and the project concluded after three consecutive participants' capture rates were greater than 80%. Thirteen participants were included in the study. Eye-tracking concordance was less than 80% reliable in the first 10 participants. The investigators hypothesised that the eye movement detection threshold was too sensitive, thus the algorithm was adjusted to reduce noise. The project concluded after the final three participants' gaze capture rates were 80%, 80% and 80.1%, respectively. This report suggests that eye-tracking technology can be reliably used with the ML1 enabled with CHARM simulator software. © Author(s) (or their employer(s)) 2021. No commercial re-use. See rights and permissions. Published by BMJ.Entities:
Keywords: simulation; simulation in healthcare; simulation-based medical education; simulation-based training; simulator design
Year: 2021 PMID: 35515734 PMCID: PMC8936533 DOI: 10.1136/bmjstel-2020-000782
Source DB: PubMed Journal: BMJ Simul Technol Enhanc Learn ISSN: 2056-6697