A Multi-class EEG-based BCI classification using Multivariate Empirical Mode Decomposition Based Filtering and Riemannian Geometry

Pramod Gaur, Ram Bilas Pachori, Hui Wang, Girijesh Prasad

Research output: Contribution to journalArticle

27 Citations (Scopus)
LanguageEnglish
Pages201-211
JournalExpert Systems with Applications
Volume95
Early online date7 Nov 2017
DOIs
Publication statusPublished - 1 Apr 2018

Keywords

  • EEG
  • BCI
  • Multivariate empirical mode decomposition
  • Riemannian geometry

Cite this

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title = "A Multi-class EEG-based BCI classification using Multivariate Empirical Mode Decomposition Based Filtering and Riemannian Geometry",
keywords = "EEG, BCI, Multivariate empirical mode decomposition, Riemannian geometry",
author = "Pramod Gaur and Pachori, {Ram Bilas} and Hui Wang and Girijesh Prasad",
note = "Compliant in UIR; evidence uploaded to 'Other files'",
year = "2018",
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AU - Gaur, Pramod

AU - Pachori, Ram Bilas

AU - Wang, Hui

AU - Prasad, Girijesh

N1 - Compliant in UIR; evidence uploaded to 'Other files'

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KW - EEG

KW - BCI

KW - Multivariate empirical mode decomposition

KW - Riemannian geometry

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JO - Expert Systems with Applications

T2 - Expert Systems with Applications

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SN - 0957-4174

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