NDLI: Multiclass Filters by a Weighted Pairwise Criterion for EEG Single-Trial Classification

Content Provider	IEEE Xplore Digital Library
Author	Haixian Wang
Copyright Year	1964
Abstract	The filtering technique for dimensionality reduction of multichannel electroencephalogram (EEG) recordings, modeled using common spatial patterns and its variants, is commonly used in two-class brain-computer interfaces (BCI). For a multiclass problem, the optimization of certain separability criteria in the output space is not directly related to the classification error of EEG single-trial segments . In this paper, we derive a new discriminant criterion, termed weighted pairwise criterion (WPC), for optimizing multiclass filters by minimizing the upper bound of the Bayesian error that is intentionally formulated for classifying EEG single-trial segments. The WPC approach pays more attention to close class pairs that are more likely to be misclassified than far away class pairs that are already well separated. Moreover, we extend WPC by integrating temporal information of EEG series. Computationally, we employ the rank-one update and power iteration technique to optimize the proposed discriminant criterion. The experiments of multiclass classification on the datasets of BCI competitions demonstrate the efficacy of the proposed method.
Sponsorship	IEEE Engineering in Medicine and Biology Society
Page Count	9
File Size	401458
Starting Page	1412
Ending Page	1420
File Format	PDF
ISSN	00189294
Volume Number	58
Issue Number	5
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-05-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electroencephalography Bayesian methods Upper bound Eigenvalues and eigenfunctions Covariance matrix Optimization Feature extraction weighted pairwise criterion (WPC) Bayesian classification error brain–computer interfaces (BCI) common spatial patterns (CSP) multiclass filters
Content Type	Text
Resource Type	Article
Subject	Biomedical Engineering

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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