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Integrated eye tracking on Magic Leap One during augmented reality medical simulation: a technical report
  1. Thomas J Caruso1,
  2. Olivia Hess1,
  3. Kenny Roy2,
  4. Ellen Wang1,
  5. Samuel Rodriguez1,
  6. Coby Palivathukal3,
  7. Nick Haber4
  1. 1 Anesthesiology, Stanford Medicine, Stanford, California, USA
  2. 2 Auckland, New Zealand
  3. 3 Los Angeles, California, USA
  4. 4 Education, Stanford University, Stanford, California, USA
  1. Correspondence to Dr Thomas J Caruso, Anesthesiology, Stanford Medicine, Stanford, CA 94304, USA; tjcaruso{at}stanford.edu

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.

  • simulation
  • simulation-based medical education
  • simulation-based training
  • simulator design
  • simulation in healthcare

Data availability statement

No data are available.

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Footnotes

  • Contributors TC contributed to the design, implementation, and analysis and writing of the manuscript. OH contributed to the writing of the manuscript. KR contributed to the design, writing and software development. EW contributed to the design and writing of the manuscript. SR contributed to the design, implementation, and analysis and writing of the manuscript. CP contributed to the design, software creation and writing of the manuscript. NH contributed to the design, implementation, and analysis and writing of the manuscript.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests TC, EW and SR are on the board of directors for Chariot Kids, a California non-profit organisation that seeks to train providers how to use technologies in healthcare and distribute technologies to sick children.

  • Provenance and peer review Not commissioned; externally peer reviewed.

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