CPS: Small: Cybersickness Mitigation and Test Suite Development

该项目旨在开发低干扰缓解选项，以缓解晕动病;即响应虚拟现实使用的晕动病症状。随着Oculus rift、Google VR和HTC Vive等几款新的虚拟现实（VR）系统在教育和培训中的使用越来越多，对晕网缓解选项的需求急剧增加。该研究的主要目的是开发一个测试套件，以便快速测试这些新的网络物理系统，并探索一套潜在的低干扰晕网缓解方案。目前，有效的缓解方案很少，而且大多数方案都是侵入性的（例如，严重限制持续时间或晕动病药物），这可能使VR培训和教育应用无法使用。这个项目追求低干扰的方法，通过探索色彩叠加，对比度和现实主义。因为人眼对不同颜色的反应不同。因为人眼对高对比度物体和低对比度物体的反应不同。最后，由于高度逼真或非常逼真的VR应用程序，过去的现实主义注意到比平均水平更少的晕机。长期目标将是开发晕电模型，以便个人用户可以使用该模型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。 该提案旨在为晕机症开发低干扰缓解选项，并为新的网络物理系统开发标准化测试套件，以便于以后进行测试和比较。在这里，Cybersickness被定义为当个体与视频显示器交互时发生的类似运动病的症状。目前的估计表明，平均而言，在人群中开始出现电脑病之前，只有15分钟的安全使用时间，对一些用户来说，只有30秒。为了有效地进行培训和教育，这些系统不能使使用者生病。研究的几个方面涉及确定可能的缓解方案，这些方案不会干扰应用程序的主要目的。 因此，研究的目标是：1）开发一个测试套件，允许快速测试新的VR系统和方法，以提供结果的一致性，2）分析一组可能的低干扰缓解选项（具体来说，现实主义的组成部分），以及3）将结果整合到一种方法中，以快速预测晕电水平。目前，有效的缓解方案很少，而且大多数方案都是侵入性的（例如，严重限制使用时间或晕动病药物）。过去的研究表明，现实主义可能是一个强大的因素，但这项研究的“为什么”和“什么”因素目前尚不清楚。由于现实主义有较少的内容限制，实验的目的是确定客观的现实主义成分，影响cybersickness，包括色调，模糊，对比度和稳定的组件。这些研究的结果，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机功能。预测模型的长期目标可用于建议个人用户适当使用VR，而不是一般的警告。所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效果，以确定其对晕机的影响。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，并在此开发之后创建“插件”功能，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受试者内设计中运行。 所有三个实验的结果将被分析，以过滤影响电脑病的现实主义成分。所有实验的结果都将与过去的电脑病研究相结合，以进一步开发一个预测模型。该奖项反映了NSF的法定使命，并被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

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.