CPS: Small: Cybersickness Mitigation and Test Suite Development

该项目寻求开发针对晕车的低干扰缓解方案；即针对虚拟现实的使用而出现类似晕车的症状。随着Oculus Rift、Google VR和HTC Vive等几种新的虚拟现实(VR)系统在教育和培训中的使用增加，现在普通民众可以使用的几种新的虚拟现实(VR)系统，对缓解晕屏的需求大幅增加。这项研究的主要目的是开发一套测试套件，以允许对这些新的网络物理系统进行快速测试，并探索一套潜在的低干扰晕屏缓解方案。目前，有效的缓解选择很少，而且这些选择中的大多数都是侵入性的(例如，严格限制持续时间或晕车药物)，这可能会使VR培训和教育应用程序无法使用。这个项目通过探索色彩叠加、对比度和真实感来追求低干扰的方法。因为人的眼睛对不同的颜色反应不同。对比度是因为人眼对高对比度和低对比度物体的反应不同。最后，由于过去高真实感或非常低真实感的VR应用程序的现实主义，注意到晕屏比平均水平要少。较长期的目标将是开发晕车模型，以便个人用户能够使用来确定特定的网络物理系统应用程序和耳机是否需要缓解选项，以及需要多少缓解选项。该提案旨在开发针对晕车的低干扰缓解方案，并为新的赛博物理系统开发标准化测试套件，以便于以后的测试和比较。晕车在这里的定义是，当个人与视频显示器互动时，出现类似晕车的症状。目前的估计表明，平均而言，在人群中开始发生网络呕吐之前，安全使用只有15分钟，对于一些用户来说，只有30秒。为了有效地进行培训和教育，这些系统不能让用户生病。研究的几个方面涉及确定不会干扰应用程序的主要目的的可能的缓解选择。因此，这项研究的目标是1)开发一套测试套件，以允许对新的VR系统和方法进行快速测试，以提供结果的一致性；2)分析一组可能的低干扰缓解选项(具体而言，是真实感的组成部分)；以及3)将结果整合到一种快速预测晕屏程度的方法中。目前，有效的缓解选择很少，而且这些选择中的大多数都是侵入性的(例如，严格限制使用时间或晕车药物)。过去的研究表明，现实主义可能是一个强有力的因素，但这项研究的“为什么”和“什么”因素目前尚不清楚。由于现实主义对内容的限制较少，因此实验旨在确定影响晕车的现实主义客观组件，包括色调、模糊、对比度和稳定化组件。这些研究的结果，例如现实主义缓解选项，可以直接用于为敏感用户创建新的应用程序。该测试套件将允许以一致的方式测试新的晕车功能。预测模型的长期目标可以用来建议个人用户适当使用VR，而不是一般性的警告。涉及的方法是建立一个测试环境，并检查不同的现实主义特征的影响，以确定它们对晕屏的影响。测试环境将通过回顾过去的交互出版物和当前的VR应用环境来构建，以确保可以考虑广泛的环境类型。缓解实验将并行运行，并遵循这一发展，以创造“插件”的能力，然后测试颜色，对比度和真实感的缓解选项。如果可能，这些缓解实验中的每一个都将在有条件的受试者设计中进行。所有三个实验的结果都将被分析，以过滤影响晕车的现实主义成分。所有实验的结果将与过去对晕机的研究合并，以进一步开发预测模型。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This project seeks to develop low-interference mitigation options for cybersickness; that is motion sickness like symptoms in response to virtual reality use. With several new virtual reality (VR) systems such as the Oculus rift, Google VR, and HTC Vive now available to the general population with increased usage in education and training, the need for cybersickness mitigation options has dramatically increased. The main purposes of the research are to develop a test suite to allow for rapid testing of these new cyberphysical systems, and to explore a potential set of low interference cybersickness mitigation options. Currently, there are very few effective mitigation options and most of these options are intrusive (e.g., severely limiting duration or motion-sickness medication) which can make VR training and education applications unusable. This project pursues to low-interference methods of by exploring color overlays, contrast, and realism. Color because human eyes respond differently to different colors. Contrast because human eyes respond differently to high versus low contrasts objects. Lastly, realism due to highly realistic or very low realistic VR applications in the past noting less cybersickness than average. The longer-term goal will be the in the development of a cybersickness model so that individual users can use to determine if, and how many, mitigation options would be needed for a particular cyberphysical system application and headset. This proposal seeks to develop low-interference mitigation options for cybersickness and a standardized test suite for new cyberphysical systems for later ease of testing and comparisons. Cybersickness is defined here as motion sickness-like symptoms occurring in individuals as they interact with video displays. Current estimates indicate, on average, that there is a mere 15 minutes of safe usage before cybersickness starts to occur in population groups, and in as little as 30 seconds for some users. To be effective in training and education, the systems must not make users ill. Several aspects of the research involve the identification of possible mitigation options that will not interfere with the primary purpose of an application. Therefore, the objectives of the research are 1) to develop a test suite to allow for rapid testing of new VR systems and methods to provide consistency in the results, 2) to analyze a possible set of low-interference mitigation options (specifically, components of realism), and 3) to integrate the results into a method to quickly predict levels cybersickness. Currently, there are very few effective mitigation options and most of these options are intrusive (e.g., severely limiting duration of use or motion-sickness medication). Past research suggests realism may be a strong factor, but the “why” and “what” factors of this research are currently unknown. Since realism has less restriction of content, experiments are designed to identify objective components of realism that affect cybersickness and include hue, blur, contrast, and stabilizing components. The results of these studies, such as the realism mitigation options, can be used directly in the creation of new applications for sensitive users. The test suite will allow for a means to test new cybersickness features in a consistent manner. The long-term goal of the predictive models can be used to advise individual users on appropriate use of VR, rather than generic warnings. The methods involved are building a test environment and examining the effect different realism features to determine their effect on cybersickness. The test environment will be built by reviewing past publications for interaction and current VR application environments to ensure a wide set of environment types can be considered. The mitigation experiment will be run in parallel and following this development to create of “plug-in” ability to then test the mitigation options of color, contrast, and realism. Each of these mitigation experiments will be run in a with-in subject design if possible. The results of all three experiments will be analyzed to filter the components of realism that affect cybersickness. The results of all experiments with be merged with past studies of cybersickness to further develop a predictive model.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.