Preliminaries of a Brain-Computer Interface Based on EEG Signal Classification
摘要
Brain-computer interfaces (BCIs) are widely used nowadays in different fields. Electroencephalography (EEG)-based BCIs are especially discussed due to their applications in both medical and entertainment usage. This paper discusses some preliminaries of such BCI for wheelchair control, namely the processing and classification of EEG signals for the recognition of different arm movements using machine learning. The focus is on feature extraction, feature selection, and classification technique. The results are analyzed by different performance measures.