標題: Using a Novel LDA-Ensemble Framework to Classification of Motor Imagery Tasks for Brain-Computer Interface Applications
作者: Chiu, Ching-Yu
Chen, Chih-Yu
Lin, Yang-Yin
Chen, Shi-An
Lin, Chin-Teng
分子醫學與生物工程研究所
光電學院
腦科學研究中心
Institute of Molecular Medicine and Bioengineering
College of Photonics
Brain Research Center
關鍵字: brain-computer interface (BCI);motor imagery;classification;linear discriminate analysis (LDA)
公開日期: 1-一月-2015
摘要: In this paper, we introduce a novel linear discriminate analysis (LDA) ensemble classifier utilizing the Mindo as a brain-computer interface (BCI) device to deal with the problem of motor imagery classification. With regard to the composition of the proposed system, we combine filter bank, sub-band common spatial pattern (SBCSP), LDA together for extracting features of EEG data and classifying the motor imagery with left or right states. In addition, we also employ a gradient descent (GD) algorithm to find the best weight associated with probability fusion function. This novel architecture not only boosts the accuracy of classification but maintains the computational efficiency of the system. Therefore, the proposed LDA-ensemble framework is able to be satisfied with each subject as demonstrated in Section III.
URI: http://dx.doi.org/10.3233/978-1-61499-484-8-150
http://hdl.handle.net/11536/150896
ISSN: 0922-6389
DOI: 10.3233/978-1-61499-484-8-150
期刊: INTELLIGENT SYSTEMS AND APPLICATIONS (ICS 2014)
Volume: 274
起始頁: 150
結束頁: 156
顯示於類別:會議論文