ABSTRACT
In virtual reality (VR), users can experience symptoms of motion sickness, which is referred to as VR sickness or cybersickness. The symptoms include but are not limited to eye fatigue, disorientation, and nausea, which can impair the VR experience of users. Though many studies have attempted to reduce the discomfort, they produced conflicting results with varying degrees of VR sickness. In particular, a visually improved VR does not necessarily result in decreased VR sickness. To understand these unexpected results, we surveyed the causes of VR sickness and measurement of symptoms. We reorganized the causes of the VR sickness into three major factors (hardware, content, and human factors) and investigated the sub-component of each factor. We then surveyed frequently used mea-sures of VR sickness, both subjective and objective approaches. We also investigated emerging approaches for reducing VR sickness and proposed a multimodal fidelity hypothesis to give an insight into future studies. Eunhee Changa, Hyun Taek Kimb, and Byounghyun Yoo Center for Imaging Media Research, Korea Institute of Science and Technology, Seoul, South Korea; Department of Psychology, Korea University, Seoul, South Korea
Nineteen articles in the data list examined the effect of the human factor on VR sickness (Table 4). Compared to other categories, the studies of human factors have tended to consider two or more variables at the same time (e.g., observing the effects of age and gender simultaneously). About half of the articles (i.e., 10 articles) investigated the effects of multiple human factors at once. While manipulating human factors, each study recorded users responses using subjective or objective measures. Questionnaires, especially SSQ, were widely used methods for the subjective measure. Meanwhile, postural sway has been investigated to compensate for the limitations of questionnaires.
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3.1.3.1. Age. A number of studies have investigated whether users age can affect the level of VR sickness. However, experiments have shown mixed results. According to Hkkinen et al. (2002), subjects aged 18 to 41 were given HMDs and experienced a virtual race environment. The result showed that an older age group showed a significant increase in SSQO scores compared to a younger age group. Park et al. (2006) also found that an older group (70 90 years) showed a higher dropout rate than a younger group (21 50 years). However, a meta-analysis by Saredakis et al. (2020) showed the opposite result. That is, individuals whose mean age lower than 35 reported a higher total SSQ score compared with the older age group. More studies are needed to explain the age effect on VR sickness since other variables such as motion sickness susceptibility and prior VR experiences are also closely related to age.
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While the age range of VR users is becoming more diverse in recent years, most research subjects were limited to young people in their 20 s. To establish a reliable safety guideline of VR devices, research on a broader age group will be required. In particular, it is important to consider a change of physical ability (e.g., vision sensitivity) as part of the developmental process.
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3.1.3.2. Gender. Inconsistent results have been drawn for the gender differences in VR sickness. Several studies showed that women are more susceptible to VR sickness and reported higher SSQ scores than men (Freitag et al., 2016; Hkkinen et al., 2002; Jaeger & Mourant, 2001; Stanney et al., 1999). However, Lawson (2014) demonstrated that it is inconclusive to claim gender differences in VR sickness based on the review of 46 previous studies (Lawson, 2014). According to his report, only 26 among 46 studies (i.e., 56.5 %) showed higher levels of VR sickness susceptibility in females compared to males. Also, a meta-analysis by Saredakis et al. (2020) did not find a significant correlation between gender and the severity of discomfort.
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