Effect of Feature and Channel Selection on EEG Classification

Ahmed Al-Ani, Akram Al-Sukker
2006 IEEE Engineering in Medicine and Biology Society. Conference Proceedings  
In this paper, we evaluate the significance of feature and channel selection on EEG classification. The selection process is performed by searching the feature/channel space using genetic algorithm, and evaluating the importance of subsets using a linear support vector machine classifier. Three approaches have been considered; (i) selecting a subset of features that will be used to represent a specified set of channels, (ii) selecting channels that are each represented by a specified set of
more » ... ures, and (iii) selecting individual features from different channels. When applied to a Brain-Computer Interface (BCI) problem, results indicate that improvement in classification accuracy can be achieved by considering the right combination of channels and features.
doi:10.1109/iembs.2006.4397869 fatcat:y7ontafprnc3tlnqkf65u7iy6e