Title :
EEG Dataset Reduction and Feature Extraction Using Discrete Cosine Transform
Author :
Birvinskas, D. ; Jusas, Vacius ; Martisius, I. ; Damasevicius, R.
Author_Institution :
Kaunas Univ. of Technol., Kaunas, Lithuania
Abstract :
Brain-Computer interface (BCI) systems require intensive signal processing in order to form control signals for electronic devices. The majority of BCI systems work by reading and interpreting cortically evoked electro-potentials across the scalp via an electro-encephalogram (EEG). An important factor affecting the efficiency of BCI is the number of EEG features. To reduce the number of features is an important way to improve the speed. In this paper, we consider application of discrete cosine transform (DCT) on EEG signals. DCT takes correlated input data and concentrates its energy in just first few transform coefficients. This method is used as a feature extraction step and allows data size reduction without losing important information. For classification we are using artificial neural networks with different number of hidden neurons and training functions. We conclude that the method can be successfully used for the feature extraction and dataset reduction.
Keywords :
bioelectric potentials; brain-computer interfaces; discrete cosine transforms; electroencephalography; feature extraction; medical signal processing; neural nets; BCI systems; DCT; EEG dataset reduction; EEG features; artificial neural networks; brain-computer interface systems; correlated input data; cortically evoked electro-potentials; data size reduction; discrete cosine transform; electro-encephalogram; electronic devices; feature extraction; hidden neurons; intensive signal processing; training functions; Artificial neural networks; Classification algorithms; Discrete cosine transforms; Electroencephalography; Feature extraction; Neurons; Training; braincomputer interface; discrete cosine transform; feature extraction;
Conference_Titel :
Computer Modeling and Simulation (EMS), 2012 Sixth UKSim/AMSS European Symposium on
Conference_Location :
Valetta
Print_ISBN :
978-1-4673-4977-2
DOI :
10.1109/EMS.2012.88