EEG-based BCI system via arithmetic and emotional imagery

Nowadays, the number of severe disabled (a totally dependent or assisted living) is dramatically increased due to the increasing rates of accident and brain disease. Therefore, this paper proposes a novel modality of brain-computer interface (BCI) system as an alternative assistive tool for the severe disabled. The use of EEG based emotional and arithmetic imagery from the pre-frontal area is employed. Linear discriminant analysis (LDA) is used to classify emotional and arithmetic imagery by using spontaneous EEG. The comparison between linear and quadric functions of LDA classifier is proposed. The results of the proposed BCI modality as well as its processing algorithm as LDA with quadric can achieve 86% accuracy function. Hence, this system can be one of the potential assistive tools for the serve disabled in their daily activities.