Motor imagery EEG signal classification with a multivariate time series approach

Motor imagery EEG signal classification with a multivariate time series approach

Abstract Background Electroencephalogram (EEG) signals record electrical activity on the scalp. Measured signals, especially EEG motor imagery signals, are often inconsistent or distorted, which compromises their classification accuracy. Achieving a reliable classification of motor imagery EEG signa...

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Bibliographic Details
Main Authors: I. Velasco, A. Sipols, C. Simon De Blas, L. Pastor, S. Bayona
Format: Article
Language:English
Published: BMC 2023-03-01
Series:BioMedical Engineering OnLine
Subjects:
EEG
Classification
Multi-resolution
Multi-variate time series
Discrete Wavelet Transform (DWT)
Online Access:https://doi.org/10.1186/s12938-023-01079-x

Internet

https://doi.org/10.1186/s12938-023-01079-x

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