Literature DB >> 17282716

One-Versus-the-Rest(OVR) Algorithm: An Extension of Common Spatial Patterns(CSP) Algorithm to Multi-class Case.

Wei Wu1, Xiaorong Gao, Shangkai Gao.   

Abstract

Extraction of relevant features that capture the invariant characteristics specific to each brain state is very important in order to implement a suitable Brain-Computer Interface (BCI) system. This paper presents an algorithm called One-Versus-the-Rest (OVR), which is an extension of a well-known method called Common Spatial Patterns (CSP) to multi-class case, to extract signal components specific to one condition from electroencephalography (EEG) dataa sets of multiple conditions. The alagorithm was previously mentioned in [7], yet without an elaborate description. In this paper, detailed mathematicaal derivation of the algorithm is given, followed by a computer simulation. The computer simulation suggests that the algorithm is capable of reconstructing the actual specific part of each condition with high quality, even when the data are contaminated with considerable noise. We also hint future possible applications of the algorithm in the context of BCI at the end of the paper.

Year:  2005        PMID: 17282716     DOI: 10.1109/IEMBS.2005.1616947

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  6 in total

1.  Probabilistic Common Spatial Patterns for Multichannel EEG Analysis.

Authors:  Wei Wu; Zhe Chen; Xiaorong Gao; Yuanqing Li; Emery N Brown; Shangkai Gao
Journal:  IEEE Trans Pattern Anal Mach Intell       Date:  2014-06-12       Impact factor: 6.226

2.  An evidence-based combining classifier for brain signal analysis.

Authors:  Saeed Reza Kheradpisheh; Abbas Nowzari-Dalini; Reza Ebrahimpour; Mohammad Ganjtabesh
Journal:  PLoS One       Date:  2014-01-02       Impact factor: 3.240

3.  Using Combination of µ,β and γ Bands in Classification of EEG Signals.

Authors:  Mina Mirnaziri; Masoomeh Rahimi; Sepidehsadat Alavikakhaki; Reza Ebrahimpour
Journal:  Basic Clin Neurosci       Date:  2013

4.  A Fully Automated Trial Selection Method for Optimization of Motor Imagery Based Brain-Computer Interface.

Authors:  Bangyan Zhou; Xiaopei Wu; Zhao Lv; Lei Zhang; Xiaojin Guo
Journal:  PLoS One       Date:  2016-09-15       Impact factor: 3.240

5.  Correlation-based common spatial pattern (CCSP): A novel extension of CSP for classification of motor imagery signal.

Authors:  Khatereh Darvish Ghanbar; Tohid Yousefi Rezaii; Ali Farzamnia; Ismail Saad
Journal:  PLoS One       Date:  2021-03-31       Impact factor: 3.240

6.  Optimization of Task Allocation for Collaborative Brain-Computer Interface Based on Motor Imagery.

Authors:  Bin Gu; Minpeng Xu; Lichao Xu; Long Chen; Yufeng Ke; Kun Wang; Jiabei Tang; Dong Ming
Journal:  Front Neurosci       Date:  2021-07-02       Impact factor: 4.677

  6 in total

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