Literature DB >> 35515734

Integrated eye tracking on Magic Leap One during augmented reality medical simulation: a technical report.

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


  12 in total

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Authors:  Joe Causer; Joan N Vickers; Ryan Snelgrove; Gina Arsenault; Adrian Harvey
Journal:  Surgery       Date:  2014-08-21       Impact factor: 3.982

2.  The use of virtual patients to teach medical students history taking and communication skills.

Authors:  Amy Stevens; Jonathan Hernandez; Kyle Johnsen; Robert Dickerson; Andrew Raij; Cyrus Harrison; Meredith DiPietro; Bryan Allen; Richard Ferdig; Sebastian Foti; Jonathan Jackson; Min Shin; Juan Cendan; Robert Watson; Margaret Duerson; Benjamin Lok; Marc Cohen; Peggy Wagner; D Scott Lind
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3.  An investigation into the effects of real vs. stimulated cases and level of experience on the distribution of visual attention during induction of general anaesthesia.

Authors:  T Grundgeiger; C Klöffel; S Mohme; T Wurmb; O Happel
Journal:  Anaesthesia       Date:  2017-02-16       Impact factor: 6.955

4.  Integrating Eye-Tracking to Augmented Reality System for Surgical Training.

Authors:  Shang Lu; Yerly Paola Sanchez Perdomo; Xianta Jiang; Bin Zheng
Journal:  J Med Syst       Date:  2020-09-29       Impact factor: 4.460

Review 5.  Eye-tracking technology in medical education: A systematic review.

Authors:  Hajra Ashraf; Mikael H Sodergren; Nabeel Merali; George Mylonas; Harsimrat Singh; Ara Darzi
Journal:  Med Teach       Date:  2017-11-26       Impact factor: 3.650

6.  Developing situation awareness amongst nursing and paramedicine students utilizing eye tracking technology and video debriefing techniques: a proof of concept paper.

Authors:  Peter O'Meara; Graham Munro; Brett Williams; Simon Cooper; Fiona Bogossian; Linda Ross; Louise Sparkes; Mark Browning; Mariah McClounan
Journal:  Int Emerg Nurs       Date:  2014-11-06       Impact factor: 2.142

7.  Joint Attention in a Laparoscopic Simulation-Based Training: A Pilot Study on Camera Work, Gaze Behavior, and Surgical Performance in Laparoscopic Surgery.

Authors:  Wilfried Krois; Carlos A Reck-Burneo; Peter Gröpel; Michael Wagner; Angelika Berger; Martin L Metzelder
Journal:  J Laparoendosc Adv Surg Tech A       Date:  2020-03-24       Impact factor: 1.878

8.  Can Eye Tracking be Used to Predict Performance Improvements in Simulated Medical Training? A Case Study in Central Venous Catheterization.

Authors:  Hong-En Chen; Rucha R Bhide; David F Pepley; Cheyenne C Sonntag; Jason Z Moore; David C Han; Scarlett R Miller
Journal:  Proc Int Symp Hum Factors Ergon Healthc       Date:  2019-09-15

9.  An observational study using eye tracking to assess resident and senior anesthetists' situation awareness and visual perception in postpartum hemorrhage high fidelity simulation.

Authors:  Arnaud Desvergez; Arnaud Winer; Jean-Bernard Gouyon; Médéric Descoins
Journal:  PLoS One       Date:  2019-08-29       Impact factor: 3.240

Review 10.  Augmented reality in medical education: a systematic review.

Authors:  Kevin S Tang; Derrick L Cheng; Eric Mi; Paul B Greenberg
Journal:  Can Med Educ J       Date:  2020-03-16
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