基于多任务和神经反馈的虚拟现实平台注意力训练系统ATVR

Menghe Zhang, Junsong Zhang, Dong Zhang
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引用次数: 5

摘要

我们提出了一种基于多任务训练场景和神经反馈原理的注意力训练系统,可以针对pc和VR平台进行训练。我们的训练系统是一个视频游戏,遵循多任务训练的原则,为所有年龄段的人设计。采用无创脑电图(EEG)装置Emotiv EPOC+采集EEG。然后利用小波包变换(WPT)提取脑电信号的特定成分。然后,我们构建了一个多类支持向量机(SVM)来对不同的注意力水平进行分类。训练系统是用Unity游戏引擎构建的,可以针对台式机和Oculus VR头显。我们还开展了应用该系统的实验,初步评价了系统的有效性。实验结果表明,该系统能普遍提高用户的多任务处理能力和注意力水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ATVR: An Attention Training System using Multitasking and Neurofeedback on Virtual Reality Platform
We present an attention training system based on the principles of multitasking training scenario and neurofeedback, which can be targeted on PCs and VR platforms. Our training system is a video game following the principle of multitasking training, which is designed for all ages. It adopts a non-invasive Electroencephalography (EEG) device Emotiv EPOC+ to collect EEG. Then wavelet package transformation(WPT) is applied to extract specific components of EEG signals. We then build a multi-class supporting vector machine(SVM) to classify different attention levels. The training system is built with the Unity game engine, which can be targeted on both desktops and Oculus VR headsets. We also launched an experiment by applying the system to preliminarily evaluate the effectiveness of our system. The results show that our system can generally improve users' abilities of multitasking and attention level.
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