An advanced bispectrum features for EEG-based motor imagery classification

作者：

Highlights：

• Variations can provide more valuable information for MI classification.

• Sensitivity of the representative bispectral features extraction method.

• Reduces the impacts of non-linear and non-Gaussian noises.

• Enhances the separability of bispectral features.

摘要

•Variations can provide more valuable information for MI classification.•Sensitivity of the representative bispectral features extraction method.•Reduces the impacts of non-linear and non-Gaussian noises.•Enhances the separability of bispectral features.

论文关键词：Motor imagery,Event-related potentials,Variations,Bispectrum,Features extraction,Classification

论文评审过程：Received 26 August 2018, Revised 27 March 2019, Accepted 9 April 2019, Available online 18 April 2019, Version of Record 24 April 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.04.021