The Impact of Mspca Signal De-Noising In Real-Time Wireless Brain Computer Interface System

Abstract

This paper presents the practical implementation of the motor imagery BCI system using MATLAB GUI. EEG signals were recorded using Mindwave Mobile Headset from one subject for two motor imagery tasks: right hand and left hand. The offline analysis showed decent performance of the combination between MSPCA de-noising of EEG se best classifier from the offline analysis was used in the online aignals and statistical features extracted from WPD sub-bands. Thssessment to classify new motor imagery EEG signals. The overall results show that the desirable de-noising results are obtained if MSPCA is applied on a data matrix containing signals that belong to one particular class.