Time-variant spatial filtering for motor imagery classification.

Full Abstract

Effective spatial filtering plays a key role in motor imagery classification. This paper presents a novel approach to spatial filtering of EEG signal by modelling time-variant spatial patterns. This is in contrast to conventional Common Spatial Pattern which assumes static spatial patterns in a motor imagery trial. We define the model such that it accounts for relatively higher order dynamics in EEG. Furthermore, we formulate the training of the model as a dual optimization problem, and we derive an iterative optimization algorithm using quadratically constrained quadratic programming. Our experimental results on healthy subjects indicates that the proposed method is able to produce higher classification accuracy.

Author information

Author/s: Zhang, Haihong (H); Wang, Chuanchu (C); Guan, Cuntai (C);

Affiliation: Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613. hhzhang(-atsign-)i2r.a-star.edu.sg

Journal and publication information

Publication Type: Evaluation Studies; Journal Article

Journal: Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference (Conf Proc IEEE Eng Med Biol Soc), published in United States. (Language: eng)

Reference: 2007-; vol 2007 (issue ) : pp 3124-7

Dates: Created 2007/11/16; Completed 2008/03/27;

PMID: 18002657, status: MEDLINE (last retrieval date: 2/18/2009, IMS Date: )

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

External Links for this article
(including full text providers, if available):

Click Electronic Full-text Provider Links to see options for finding the electronic full text links to this article. Note there may be a subscription or fee required for access to the full text. See our FAQ for information on finding FREE full text articles.

This article may also be located in paper journal collections available in many libraries. Use the Journal and Publication Information above to find the full article.