EEG-Based VR Scene Adaptive Generation System for Regulating Emotion

Hui Liang, Shiqing Liu, Yi Wang, Junjun Pan, Jialin Fu, Yingkai Yuan
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Abstract

Research based on electroencephalogram (EEG) and virtual reality (VR) has developed rapidly in recent years. The integration of EEG and VR technology has been broadly employed in psychological intervention to treat various psychological conditions and alleviate stress. At present, there exist commercial-level EEG emotion recognition products, however, research on the correlation between the content of VR scenarios and emotions remains unavailable. Therefore, this work investigates VR scene construction based on EEG, which incorporates the recovery environment theory and virtual reality technology to construct different three-dimensional dynamic virtual reality interaction scenes. EEG equipment constructs an emotion-adaptive VR system based on EEG signals with the aid of VR interaction equipment. Herein, EEG data feedback was applied to automatically generate VR scenes, and the experimental findings revealed that the system has certain feasibility and application value.
基于脑电图的情绪调节VR场景自适应生成系统
近年来,基于脑电图(EEG)和虚拟现实(VR)的研究发展迅速。脑电图与虚拟现实技术的结合已广泛应用于心理干预,治疗各种心理状况,缓解压力。目前已经有了商业层面的EEG情绪识别产品,但是对于VR场景内容与情绪之间的相关性研究尚缺乏。因此,本文研究了基于脑电图的虚拟现实场景构建,将恢复环境理论与虚拟现实技术相结合,构建不同的三维动态虚拟现实交互场景。脑电图设备借助虚拟现实交互设备,以脑电图信号为基础,构建了一个情绪自适应的虚拟现实系统。本文将脑电数据反馈应用于虚拟现实场景的自动生成,实验结果表明该系统具有一定的可行性和应用价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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