Caruso Thomas J, Hess Olivia, Roy Kenny, Wang Ellen, Rodriguez Samuel, Palivathukal Coby, Haber Nick
Anesthesiology, Stanford Medicine, Stanford, California, USA.
Auckland, New Zealand.
BMJ Simul Technol Enhanc Learn. 2021 Feb 24;7(5):431-434. doi: 10.1136/bmjstel-2020-000782. eCollection 2021.
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.
增强现实（AR）已被作为一种临床教学工具进行研究，然而，集成在AR医学模拟器中的眼动追踪功能的研究却很有限。最近开发的Chariot增强现实医学（CHARM）模拟器将实时通信集成到了便携式医学模拟器中。本项目的目的是优化CHARM模拟器在Magic Leap One（ML1）上的注视追踪功能。采用便利抽样法招募了18岁及以上的成年人。为参与者提供了一个ML1头戴式设备，该设备投射出患者、病床和监视器的全息图。通过录音指导他们注视该场景中的变量。将来自ML1输出的参与者注视目标与录音中指定的注视点进行比较。先验研究者计划对眼动追踪软件进行迭代修改，直到捕获率达到80%。连续两名捕获率低于80%的参与者触发了软件修改，在连续三名参与者的捕获率大于80%后，该项目结束。13名参与者被纳入研究。在前10名参与者中，眼动追踪一致性的可靠性低于80%。研究者推测眼动检测阈值过于敏感，因此对算法进行了调整以减少噪声。在最后三名参与者的注视捕获率分别为80%、80%和80.1%后，该项目结束。本报告表明，眼动追踪技术可以与启用了CHARM模拟器软件的ML1可靠地配合使用。
