Signal Enhancement and Dimensionality Reduction by XDAWN and Compressive Sensing Models

A brain-computer interface (BCI) is a communication system that allows the brain to control external devices. In this paper, we propose a method based on the XDA WN and compressive sensing (CS) models to enhance the performance of online BCI. The method aims to generate features for signal enhancement and dimensionality reduction of motion-onset visual evoked potentials (MVEP). The experimental results of data analysis demonstrate the advantages of the proposed method.