Decoding non-motor imagery tasks with non-invasive EEG based brain-computer interface: a review

Abstract

Electroencephalogram (EEG) based Brain-Computer Interface (BCI) applications are mostly proposed to aid people with motor disabilities. However, recent research focuses on EEG-based BCI development for non-clinical applications such as gaming. Using non-motor imagery has shown significant potential to provide control commands in many BCI-related applications. Researchers have explored many techniques in the process of decoding non-motor imagery tasks using EEG. This review article aims to provide an overview of the methods used in data acquisition, preprocessing, feature extraction, and classification phases in related work to EEGbased BCI. This will help researchers choose the techniques with the most potential after examining their benefits and drawbacks. This paper will also provide future directions for further improving decoding non-motor imagery tasks through EEG-based BCI for practical applications.