EEG-based attention recognition using machine learning - Sun, Haoqi (2017)
Attention is constantly required in many daily life tasks. Attention-related behavior, such as driving distraction, has been reported as a major reason in traffic accidents. Therefore, the recognition of attention can enhance task performance. Electroencephalogram (EEG) is used to study attention, since it provides a direct measure of the brain activity with high temporal resolution at 1-10ms. In this thesis, we study the recognition of selective attention and sustained attention (vigilance) using machine learning.