Abstract

Cybersickness refers to a group of uncomfortable symptoms experienced in virtual reality (VR). Among several theories of cybersickness, the subjective vertical mismatch (SVM) theory focuses on an individual’s internal model, which is created and updated through past experiences. Although previous studies have attempted to provide experimental evidence for the theory, most approaches are limited to subjective measures or body sway. In this study, we aimed to demonstrate the SVM theory on the basis of the participant’s eye movements and investigate whether the subjective level of cybersickness can be predicted using eye-related measures. 26 participants experienced roller coaster VR while wearing a head-mounted display with eye tracking. We designed four experimental conditions by changing the orientation of the VR scene (upright vs. inverted) or the controllability of the participant’s body (unrestrained vs. restrained body). The results indicated that participants reported more severe cybersickness when experiencing the upright VR content without controllability. Moreover, distinctive eye movements (e.g. fixation duration and distance between the eye gaze and the object position sequence) were observed according to the experimental conditions. On the basis of these results, we developed a regression model using eye-movement features and found that our model can explain 34.8% of the total variance of cybersickness, indicating a substantial improvement compared to the previous work (4.2%). This study provides empirical data for the SVM theory using both subjective and eye-related measures. In particular, the results suggest that participants’ eye movements can serve as a significant index for predicting cybersickness when considering natural gaze behaviors during a VR experience.

中文翻译：

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在基于HMD的虚拟现实中基于用户的凝视行为预测网络疾病

摘要

晕车病是指在虚拟现实（VR）中遇到的一组不适症状。在几种网络疾病理论中，主观垂直失配（SVM）理论侧重于个人的内部模型，该模型是根据过去的经验创建和更新的。尽管以前的研究试图为该理论提供实验证据，但大多数方法仅限于主观测量或摇摆。在这项研究中，我们旨在基于参与者的眼睛运动来证明SVM理论，并研究是否可以使用与眼睛相关的措施来预测网络疾病的主观水平。26位参加者在佩戴带有眼动追踪器的头戴显示器时体验了过山车VR。我们通过更改VR场景的方向（垂直vs.垂直）设计了四个实验条件。倒置）或参与者身体的可控性（不受约束的身体与受约束的身体）。结果表明，参与者在体验不受控制的虚拟VR内容时报告了更严重的网络疾病。此外，根据实验条件观察到独特的眼睛运动（例如，注视持续时间和注视与物体位置序列之间的距离）。基于这些结果，我们开发了一种利用眼动特征的回归模型，发现我们的模型可以解释网络疾病总方差的34.8％，表明与先前的研究（4.2％）相比有实质性的改进。这项研究使用主观和与眼睛相关的措施为SVM理论提供了经验数据。特别是，