DocumentCode :
2948268
Title :
Classification of movement EEG with local discriminant bases
Author :
Ince, Nuri Firat ; Tewfik, Ahmed ; ARICA, Sami
Author_Institution :
Dept. of Electr. & Electron. Eng., Cukurova Univ., Adana, Turkey
Volume :
5
fYear :
2005
fDate :
18-23 March 2005
Abstract :
We use local discriminant bases and linear discriminant analysis to classify EEG of left and right hand movement execution and imagination. The local discriminant bases adaptively segment and extract features from real and imagined movement EEG (2003 BCI competition) using cosine packets and Kullback-Leibler, Euclidean and Hellinger class separability (CS) criteria. We also tried principal component analysis (PCA) as another feature reduction method. In our case, CS ordered coefficients resulted in lower classification error than PCA using a smaller number of coefficients. We observed that the most discriminative components were located on the post movement beta and alpha synchronization. Pre-movement features were also selected by the algorithm. We believe that these segments correspond to the mental state and strategy of the subject during the movement execution/imagination. The main advantage of the algorithm is that it adaptively finds these physiological states in an ongoing EEG. This may eliminate the inter- and intra-subject variability. The average error rate of the classification was 12.7% for movement execution and 14.2% for movement imagination. Accordingly, the algorithm would be the 3rd best in the 2003 BCI (brain-computer interface) competition.
Keywords :
electroencephalography; error statistics; feature extraction; medical signal processing; principal component analysis; signal classification; synchronisation; user interfaces; Euclidean criterion; Hellinger criterion; Kullback-Leibler criterion; PCA; adaptive feature extraction; adaptive feature segmentation; brain-computer interface; class separability criteria; classification error rate; cosine packets; hand movement execution; hand movement imagination; linear discriminant analysis; local discriminant bases; movement EEG classification; physiological states; post movement beta-alpha synchronization; principal component analysis; Brain computer interfaces; Communication system control; Electroencephalography; Error analysis; Feature extraction; Frequency; Image segmentation; Linear discriminant analysis; Principal component analysis; Vector quantization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP '05). IEEE International Conference on
ISSN :
1520-6149
Print_ISBN :
0-7803-8874-7
Type :
conf
DOI :
10.1109/ICASSP.2005.1416328
Filename :
1416328
Link To Document :
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