ATVR: An Attention Training System using Multitasking and Neurofeedback on Virtual Reality Platform

EasyChair Preprint 1746

Abstract

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.

Keyphrases: Attention training, Neurofeedback, Virtual Reality, multitasking

@booklet{EasyChair:1746,
  author    = {Menghe Zhang and Junsong Zhang and Dong Zhang},
  title     = {ATVR: An Attention Training System using Multitasking and Neurofeedback on Virtual Reality Platform},
  howpublished = {EasyChair Preprint 1746},
  year      = {EasyChair, 2019}}