In this study, an electroencephalogram (EEG) analysis system is proposed for single-trial classification of both motor imagery (MI) and finger-lifting EEG data. Applying event-related brain potential (ERP) data acquired from the sensorimotor cortices, the system mainly consists of three procedures; enhanced active segment selection, feature extraction, and classification. In addition to the original use of continuous wavelet transform (CWT) and Student 2-sample t statistics, the two-dimensional (2D) anisotropic Gaussian filter further refines the selection of active segments. The multiresolution fractal features are then extracted from wavelet data by using proposed modified fractal dimension. Finally, the support vector machine (SVM) is used for classification. Compared to original active segment selection, with several popular features and classifier on both the MI and finger-lifting data from 2 data sets, the results indicate that the proposed method is promising in EEG classification.
NicolaouNGeorgiouJ. The use of permutation entropy to characterize sleep electroencephalograms. Clin EEG Neurosci. 2011;42(1):24–28.
2.
XuJZhaoSZZhangHSZhengCX. Decreased delta event-related synchronization in patients with early vascular dementia. Clin EEG Neurosci. 2011;42(1):53–58.
3.
AhmadlouMAdeliH. Fuzzy synchronization likelihood with application to attention-deficit/hyperactivity disorder. Clin EEG Neurosci. 2011; 42(1): 6–13.
4.
ParraLAlvinoCTangACLinear spatial integration for single trial detection in encephalography. Neuroimage2002;7(1):223–230.
5.
BayramABayraktarogluZKarahanESimultaneous EEG/fMRI analysis of the resonance phenomena in steady-state visual evoked responses. Clin EEG Neurosci. 2011;42(2):98–106.
6.
HsuWY. EEG-based motor imagery classification using neuro-fuzzy prediction and wavelet fractal features. J Neurosci Meth. 2010;189(2):295–302.
7.
WolpawJRBirbaumerNHeetderksWJBrain-computer interface technology: a review of the first international meeting. IEEE Trans Rehab Eng. 2000;8(2):164–173.
8.
HsuWY. Continuous EEG signal analysis for asynchronous BCI application. Int J Neural Syst. 2011;21(4):335–350.
HsuWY. Application of multiscale amplitude modulation features and FCM clustering to brain-computer interface. Clin EEG Neurosci. 2011;43(1):32–38.
13.
Flor-HenryP. EEG analysis of male to female transsexuals: discriminant function and source analysis. Clin EEG Neurosci. 2010;41(4):219–222.
14.
HsuWY. Fuzzy hopfield neural network clustering for single-trial motor imagery EEG classification. Expert Syst Appl. 2012;39(1):1055–1061.
15.
PfurtschellerGNeuperChFlotzingerDPregenzerM. EEG based discrimination between imagination of right and left hand movement. Electroenc Clin Neurophys. 1997;103(5):1–10.
16.
KellySBurkeDChazalPdeReillyR. Parametric models and spectral analysis for classification in brain-computer interfaces. Proc 14th Int. Digit Signal Process. 2002;1:307–310.
17.
MandelbrotBB. Fractal Geometry of Nature. San Francisco, CA: Freeman Press, 1982.
18.
DemiralpTYordanovaJKolevVAdemogluADevrimMSamarVJ. Time-frequency analysis of single-sweep event-related potentials by means of fast wavelet transform. Brain Lang. 1999;66(1):129–145.
19.
HsuWYPoonWFPSunYN. Automatic seamless mosaicing of microscopic images: enhancing appearance with color degradation compensation and wavelet-based blending. J Microsc-Oxford. 2008;231(3):408–418.
20.
GreeneBRFaulSMarnaneWPLightbodyGKorotchikovaIBoylanGB. A comparison of quantitative EEG features for neonatal seizure detection. Clin Neurophysiol. 2008;119(6):1248–1261.
21.
HsuWY. Analytic differential approach for robust registration of rat brain histological images. Microsc Res Techniq. 2011;74(6):523–530.
22.
HsuWYLinCCJuMSSunYN. Wavelet-based fractal features with active segment selection: application to single-trial EEG data. J Neurosci Meth. 2007;163(1):145–160.
23.
BoserBEGuyonIMVapnikV. A training algorithm for optimal margin classifiers. In: Proceedings of the 5th Annual Workshop on Computational Learning Theory. New York, NY: ACM Press; 1992:144–152.
24.
SchloglAKeinrathCSchererRPfurtschellerG. Estimating the mutual information of an EEG-based brain computer interface. Biomedizinische Technik2002;47(1-2):3–8.
