Park Seo-Yoon, Koo Dong-Kyun
Department of Physical Therapy, College of Health and Welfare, Woosuk University, 443 Samnye-ro, Samnye-eup, Wanju-gun 55338, Republic of Korea.
University-Industrial Cooperation Corps of HiVE Center, Wonkwang Health Science University, 514, Iksan-daero, Iksan-si 54538, Republic of Korea.
Sensors (Basel). 2025 Jan 2;25(1):215. doi: 10.3390/s25010215.
Virtual reality (VR) technology has gained popularity across various fields; however, its use often induces cybersickness, characterized by symptoms such as dizziness, nausea, and eye strain. This study investigated the differences in cybersickness levels and head movement patterns under three distinct VR viewing conditions: dynamic VR (DVR), static VR (SVR), and a control condition (CON) using a simulator. Thirty healthy adults participated, and their head movements were recorded using the Meta Quest 2 VR headset and analyzed using Python. The Virtual Reality Sickness Questionnaire (VRSQ) assessed subjective cybersickness levels. The results revealed that the SVR condition induced the highest VRSQ scores (M = 58.057), indicating the most severe cybersickness symptoms, while the DVR condition elicited significantly higher values in head movement variables, particularly in the coefficient of variation (CV) and integral values of head position along the vertical axis, and mean velocity ( < 0.05). These findings suggest that VR content characteristics directly influence users' head movement patterns, closely related to cybersickness occurrence and severity. This study highlights the importance of analyzing head movement patterns in cybersickness research and provides insights for VR content design.
虚拟现实(VR)技术已在各个领域得到广泛应用;然而,其使用往往会引发晕动病,症状包括头晕、恶心和眼疲劳等。本研究使用模拟器调查了在三种不同的VR观看条件下(动态VR(DVR)、静态VR(SVR)和对照条件(CON))晕动病水平和头部运动模式的差异。30名健康成年人参与了研究,他们的头部运动通过Meta Quest 2 VR头显进行记录,并使用Python进行分析。通过虚拟现实晕动病问卷(VRSQ)评估主观晕动病水平。结果显示,SVR条件下的VRSQ得分最高(M = 58.057),表明晕动病症状最严重,而DVR条件下头部运动变量的值显著更高,特别是垂直轴上头部位置的变异系数(CV)和积分值以及平均速度(<0.05)。这些发现表明,VR内容特征直接影响用户的头部运动模式,而头部运动模式与晕动病的发生和严重程度密切相关。本研究强调了在晕动病研究中分析头部运动模式的重要性,并为VR内容设计提供了见解。