Brain Computer Interface-Based Signal Processing Techniques for Feature Extraction and Classification of Motor Imagery Using EEG: A Literature Review

A communication path for people having severe neural disorders is provided by Brain Computer Interaction. The Brain–Computer Interface in an electroencephalogram important and challenging one managing non-stationary EEG signals. signals are more vulnerable to noise artifacts. Motor Imagery-based used as a channel with who have no muscular activity. For well-established accurate BCI system, two steps been MI-BCI, such feature extraction classification. Spectral methods spatial the methods. classifiers translate features into device commands. Linear Discriminant Analysis most widely classification algorithm. So far, Support Vector Machine has method. In recent studies, Deep Neural Networks Convolutional used. this study, approaches well signal motor imagery brain computer interface thoroughly reviewed presented.