Abstract:
Objective.Presence is an important aspect of user experience in virtual reality (VR). It corresponds to the illusion of being physically located in a virtual environment (VE). This feeling is usually measured through questionnaires that disrupt presence, are subjective and do not allow for real-time measurement. Electroencephalography (EEG), which measures brain activity, is increasingly used to monitor the state of users, especially while immersed in VR.Approach.In this paper, we present a way of evaluating presence, through the measure of the attention dedicated to the real environment via an EEG oddball paradigm. Using breaks in presence, this experimental protocol constitutes an ecological method for the study of presence, as different levels of presence are experienced in an identical VE.Main results.Through analysing the EEG data of 18 participants, a significant increase in the neurophysiological reaction to the oddball, i.e. the P300 amplitude, was found in low presence condition compared to high presence condition. This amplitude was significantly correlated with the self-reported measure of presence. Using Riemannian geometry to perform single-trial classification, we present a classification algorithm with 79% accuracy in detecting between two presence conditions.Significance.Taken together our results promote the use of EEG and oddball stimuli to monitor presence offline or in real-time without interrupting the user in the VE.
摘要:
目的:存在是虚拟现实中用户体验的一个重要方面。它对应于物理上位于虚拟环境中的错觉。这种感觉通常是通过破坏存在的问卷来衡量的,是主观的,不允许实时测量。脑电图(EEG),测量大脑活动,越来越多地用于监控用户的状态,尤其是沉浸在虚拟现实中。
方法:在本文中,我们提出了一种评估存在的方法,通过EEG怪球范例来衡量对真实环境的关注。使用存在中断(BiP),这个实验方案构成了一种研究存在的生态方法,因为在相同的虚拟环境中体验到不同级别的存在。
结果:通过分析18名参与者的脑电图数据,对怪胎的神经生理反应显着增加,即,P300振幅,与高存在条件相比,在低存在条件下发现。该幅度与自我报告的存在度量显着相关。使用黎曼几何进行单试验分类,我们提出了一种分类算法,在检测两个存在条件之间具有79%的准确率。
结论:总之,我们的结果促进了使用EEG和oddball刺激来离线或实时监测存在,而不会中断虚拟环境中的用户。