A Real Time EEG-Based Neurofeedback platform for Attention Training

Reza Abiri (1) , Xiaopeng Zhao (1) , Yang Jiang (2)

1 The University of Tennessee [Knoxville]
2 UK - University of Kentucky

A Brain Computer Interface (BCI) system as a closed-loop system can be used as a neurofeedback platform in neuro-rehabilitation programs. Here, we have developed a new attention-based neurofeedback system using noninvasive brainwaves signals. Scalp Electroencephalography (EEG) signals of a subject were collected in real-time during some minutes of sustained attention tasks in which the subject was looking at a sequence of visual stimuli pictures composited of two categories (Scene & Face). The attentional states and levels of the subject for the targeted picture will be determined by analysis of EEG data. Then, the EEG attention level classifier was fed back to our BCI platform while the same visual stimuli neurofeedback is given to the subject. It was confirmed that the transparency of a targeted picture can be controlled based on subject's attention level. The developed platform can have potential application in attention enhancement of patients with cognitive disorders.

Domaines: Biotechnologie; Interface homme-machine [cs.HC]; Systèmes et contrôle [cs.SY]

Reza Abiri, Xiaopeng Zhao, Yang Jiang. A Real Time EEG-Based Neurofeedback platform for Attention Training. Biomedical Engineering Society Annual Meeting (BMES 2016), Oct 2016, Minneapolis, MN, United States. ⟨hal-01574291⟩