File(s) under permanent embargo
Motor Imagery Data Classification for BCI Application Using Wavelet Packet Feature Extraction
chapter
posted on 2014-10-24, 00:00 authored by Imali HettiarachchiImali Hettiarachchi, Thanh Thi NguyenThanh Thi Nguyen, Saeid NahavandiThe noninvasive brain imaging modalities have provided us an extraordinary means for monitoring the working brain. Among these modalities, Electroencephalography (EEG) is the most widely used technique for measuring the brain signals under different tasks, due to its mobility, low cost, and high temporal resolution. In this paper we investigate the use of EEG signals in brain-computer interface (BCI) systems.
We present a novel method of wavelet packet-based feature extraction and classification of motor imagery BCI data. The prominent discriminant features from a redundant wavelet feature set is selected using the receiver operating characteristic (ROC) curve and fisher distance criterion. The BCI competition 2003 data set Ib is used to evaluate a number of classification algorithms. The results indicate that ROC is able to produce better classification accuracy as compared with that from the fisher distance criterion.
We present a novel method of wavelet packet-based feature extraction and classification of motor imagery BCI data. The prominent discriminant features from a redundant wavelet feature set is selected using the receiver operating characteristic (ROC) curve and fisher distance criterion. The BCI competition 2003 data set Ib is used to evaluate a number of classification algorithms. The results indicate that ROC is able to produce better classification accuracy as compared with that from the fisher distance criterion.
History
Event
International Conference on Neural Information ProcessingTitle of book
Neural information processing : 21st International Conference ICONIP 2014 Kuching, Malaysia, November 3-6, 2014 Proceedings, Part IIIVolume
8836Series
Lecture notes in computer scienceChapter number
63Pagination
519 - 526Publisher
SpringerLocation
Kuching, MalaysiaPlace of publication
Berlin, GermanyPublisher DOI
Start date
2014-11-03End date
2014-11-06ISSN
0302-9743eISSN
1611-3349ISBN-13
9783319126425Language
engPublication classification
B Book chapter; B1 Book chapterCopyright notice
2014, SpringerExtent
83Editor/Contributor(s)
C Loo, K Yap, K Wong, A Teoh, K HuangUsage metrics
Categories
No categories selectedKeywords
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC