T. Caruso, Olivia Hess, Kenny Roy, Ellen Wang, S. Rodriguez, Coby Palivathukal, N. Haber
{"title":"Integrated eye tracking on Magic Leap One during augmented reality medical simulation: a technical report","authors":"T. Caruso, Olivia Hess, Kenny Roy, Ellen Wang, S. Rodriguez, Coby Palivathukal, N. Haber","doi":"10.1136/bmjstel-2020-000782","DOIUrl":null,"url":null,"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.","PeriodicalId":44757,"journal":{"name":"BMJ Simulation & Technology Enhanced Learning","volume":null,"pages":null},"PeriodicalIF":1.1000,"publicationDate":"2021-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMJ Simulation & Technology Enhanced Learning","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1136/bmjstel-2020-000782","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 1
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.
增强现实(AR)已被研究作为临床教学工具,然而眼动追踪功能集成在AR医学模拟器有限的研究。最近开发的战车增强现实医疗(CHARM)模拟器将实时通信集成到便携式医疗模拟器中。这个项目的目的是改进Magic Leap One (ML1)上的CHARM模拟器的注视跟踪功能。采用方便抽样方法招募18岁及以上的成年人。参与者被提供了一个ML1头戴式耳机,该耳机投射了病人、床和监视器的全息图。他们通过录音被指示盯着这个场景中的变量。将ML1输出的被试凝视目标与音频记录的指定凝视点进行比较。先验研究人员计划对眼球追踪软件进行反复修改,直到达到80%的捕获率。连续两个捕获率低于80%的参与者触发软件修改,连续三个参与者捕获率大于80%后项目结束。13名参与者参与了这项研究。在前10名参与者中,眼球追踪一致性的可靠性低于80%。研究人员假设眼动检测阈值过于敏感,因此对算法进行了调整以降低噪声。当最后三名参与者的凝视捕捉率分别达到80%、80%和80.1%时,项目结束。该报告表明,眼动追踪技术可以可靠地使用具有CHARM模拟器软件的ML1。