Recognition of motor imagery left and right hand movement using EEG

Brain computer interface (BCI) is one of the recent trends for the development of electroencephalogram (EEG) signal based, a human controlling device for a motor disable person. This paper aims to detect the left and right hand movement of motor disable person using EEG signals with the usage of Independent component analysis (ICA) technique and support vector machine (SVM) classifier. For signal classification, the amalgamations of the frequency domain and time domain features are used. The proposed system obtains an accuracy of 83% to 90% by using the standard publicly available EEG database, where some existing methods are implemented on the same datasets to detect same, there are obtaining less than 80% accuracy.