EEG Based Classification of Hand Movements using BCI

Abstract

-Brain interface computer (BCI) is new area of disabled people. Detection of imagination of left is made in my project and it can used for external devices such as robotic arm. The electrical activity can be picked up from scalp electroencephalogram electrodes. Here we have collected signals using Enobio 8 software. The collected signals are given to NE_Viewer filter to get Filtered data. The filtered data is then taken to extract from time domain information in both ALPHA and BETA bands using wavelet transform. The ALPHA and BETA waves are used and extracted some of the parameters such as power, standard deviation, and variance. The LDA classifier is used to classify the Imagination of left and right hand movements. In our project we have taken 40 samples for training data set and for testing phase we have taken 10 samples for testing and we have achieved 90% of accuracy.