Automated and Adaptive Feature Extraction for Brain-Computer Interfaces by using Wavelet Packet

Author

Yan, Guo-Zheng ; Yang, Bang-hua ; Chen, Shuo

Author_Institution

Inf. & Electr. Eng., Shanghai Jiao Tong Univ.

fYear

2006

fDate

13-16 Aug. 2006

Firstpage

4248

Lastpage

4251

Abstract

An automated and adaptive feature extraction method is discussed in this paper. The method is based on the wavelet packet transform (WPT) and used to extract features of electroencephalogram (EEG) signals for brain computer interfaces (BCIs). The idea is to employ the best basis algorithm to select the most appropriate wavelet and the best wavelet packet basis automatically. Meanwhile, both the selected wavelet and the selected basis are adaptive to each EEG channel and each subject. The effectiveness of the method is verified by discriminating three different motor imagery tasks of six subjects

Keywords

electroencephalography; feature extraction; medical image processing; wavelet transforms; EEG channel; automated feature extraction; brain-computer interfaces; electroencephalogram signals; wavelet packet transform; Basis algorithms; Brain computer interfaces; Cybernetics; Electroencephalography; Feature extraction; Fuzzy sets; Humans; Machine learning; Psychology; Signal analysis; Wavelet packets; Wavelet transforms; Brain-computer interface (BCI); Electroencephalogram (EEG); Fuzzy sets; Wavelet packet transform (WPT);

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2006 International Conference on

Conference_Location

Dalian, China

Print_ISBN

1-4244-0061-9

Type

conf

DOI

10.1109/ICMLC.2006.259006

Filename

4028818