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.