Title :
A Novel Method of De-noising and Classifying on Mental EEG of Imaging Left-Right Hands Movement
Author :
Wu, Shaochun ; Song, Duhong ; Li, Mingdong ; Xu, Lingyu
Author_Institution :
Sch. of Comput. Eng. & Sci., Shanghai Univ. Shanghai, Shanghai, China
Abstract :
After analyzing the current wavelet threshold de-noising methods and independent component analysis (ICA) methods in EEG, this paper proposed a novel method for EEG de-noising which combines the new threshold de-noising method with ICA method and implicates it to deal with mental EEG of imaging left-right hands movement, and then classifies the signal by support vector machine (SVM). The correct classification rate of 89.93% is achieved by the approach in this paper.
Keywords :
biomechanics; electroencephalography; image classification; image denoising; image segmentation; independent component analysis; medical image processing; support vector machines; wavelet transforms; ICA method; image classification; independent component analysis; left-right hands movement EEG imaging; support vector machine; wavelet threshold de-noising method; Electrocardiography; Electroencephalography; Electrooculography; Independent component analysis; Noise level; Noise reduction; Support vector machine classification; Support vector machines; Wavelet coefficients; Wavelet transforms; De-noising; EEG; ICA; Wavelet transform;
Conference_Titel :
Bioinformatics, Systems Biology and Intelligent Computing, 2009. IJCBS '09. International Joint Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3739-9
DOI :
10.1109/IJCBS.2009.87
