Feature Extraction of EEG Waves Based on Morphological Multiresolution Analysis

Electroencephalograph (EEG) recordings during right and left hand motor imagery can be used to move a cursor to a target on a computer screen. Such an EEG-based brain-computer interface (BCI) can provide a new communication channel to replace an impaired motor function. It can be used by e.g., handicap users with amyotrophic lateral sclerosis (ALS). In this paper, feature extraction based on morphological multiresolution analysis is introduced to discriminate the EEG signals recorded during left and right hand motor imagery, and oddball task. The mixture features in the brain wave signal of single channel is able to separate to various bands. The structural function to decide the filter characteristic is discussed using the experimental studies.