Brain-Based Computer Interfaces Using Eeg Sensor

Abstract

Electroencephalography (EEG)-based brain-computer interfaces (BCIs), particularly those using motor-imagery (MI) data, have
the potential to become groundbreaking technologies in both clinical and entertainment settings. MI data is generated when
a subject imagines the movement of a limb. This paper reviews state-of-the-art signal processing techniques for MI EEG-based
BCIs, with a particular focus on the feature extraction, feature selection and classification techniques used. It also summarizes
the main applications of EEG-based BCIs, particularly those based on MI data, and finally presents a detailed discussion of the
most prevalent challenges impeding the development and commercialization of EEG-based BCIs