Optimizing feature vectors and removal unnecessary channels in BCI speller application - Journal of Biomedical Science and Engineering

JBiSE > Vol.6 No.10, October 2013

Optimizing feature vectors and removal unnecessary channels in BCI speller application ()

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DOI: 10.4236/jbise.2013.610121 5,099 Downloads 7,194 Views Citations

Author(s)

Bahram Perseh, Majid Kiamini

Affiliation(s)

College of Electrical Engineering, Zanjan University, Zanjan, Iran.
Department of Biophysics, Zanjan University of Medical Sciences, Zanjan, Iran.

ABSTRACT

In this paper we will discuss novel algorithms to develop the brain-computer interface (BCI) system in speller application based on single-trial classification of electroencephalogram (EEG) signal. The idea is to employ proper methods for reducing the number of channels and optimizing feature vectors. Removal unnecessary channels and reducing feature dimension result in cost decrement, time saving and improve the BCI implementation eventually. Optimal channels will be gotten after two stages sifting. In the first stage, the channels reduced up to 30% based on channels of the important event related potential (ERP) components and in the next stage, optimal channels were extracted by backward forward selection (BFS) algorithm. Also we will show that suitable single-trial analysis requires applying proper feature vector that was constructed by recognizing important ERP components, so as to propose an algorithm to distinguish less important features in feature vectors. F-Score criteria used to recognize effective features which created more discrimination between different classes and feature vectors were reconstructed based on effective features. Our algorithm has tested on dataset II of BCI competition III. The results show that we achieve accuracy up to 31% in single-trial, which is better than the performance of winner who is in this competition (about 25.5%). Also we use simple classifier and few channels to compute output performances while more complicated classifier and all channels are used by them.

KEYWORDS

Brain Computer Interface (BCI); Speller Application; Event Related Potential (ERP); ERP Components; Channel Selection; Feature Extraction

Share and Cite:

Perseh, B. and Kiamini, M. (2013) Optimizing feature vectors and removal unnecessary channels in BCI speller application. Journal of Biomedical Science and Engineering, 6, 973-981. doi: 10.4236/jbise.2013.610121.

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