DocumentCode :
1829783
Title :
Wavelet Packet Decomposition of a New Filter -Based on Underlying Neural Activity- for ERP Classification
Author :
Raiesdana, S. ; Shamsollahi, M.B. ; Hashemi, M.R. ; Rezazadeh, I.
Author_Institution :
Islamic Azad Univ., Qazvin
fYear :
2007
fDate :
22-26 Aug. 2007
Firstpage :
1876
Lastpage :
1879
Abstract :
This paper introduces a wavelet packet algorithm based on a new wavelet like filter created by a neural mass model in place of wavelet. The hypothesis is that the performance of an ERP based BCI system can be improved by choosing an optimal wavelet derived from underlying mechanism of ERPs. The wavelet packet transform has been chosen for its generalization in comparison to wavelet. We compared the performance of proposed algorithm with existing standard wavelets as Db4, Bior4.4 and Coif3 in wavelet packet platform. The results showed a lowest cross validation error for the new filter in classification of two different kinds of ERP datasets via a SVM classifier.
Keywords :
neurophysiology; ERP classification; event related potentials; neural activity; neural mass model; wavelet packet algorithm; wavelet packet decomposition; Electroencephalography; Enterprise resource planning; Fourier transforms; Frequency; Low pass filters; Space stations; Spatial resolution; Wavelet analysis; Wavelet packets; Wavelet transforms; Algorithms; Computer Simulation; Data Interpretation, Statistical; Electric Impedance; Equipment Design; Evoked Potentials; Humans; Models, Theoretical; Neural Networks (Computer); Regression Analysis; Reproducibility of Results; Signal Processing, Computer-Assisted; Software;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE
Conference_Location :
Lyon
ISSN :
1557-170X
Print_ISBN :
978-1-4244-0787-3
Type :
conf
DOI :
10.1109/IEMBS.2007.4352681
Filename :
4352681
Link To Document :
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