Identification of Anisomerous Motor Imagery EEG Signals Based on Complex Algorithms

Motor imagery (MI) electroencephalograph (EEG) signals are widely applied in brain-computer interface (BCI). However, classified MI states are limited, and their classification accuracy rates are low because of the characteristics of nonlinearity and nonstationarity. This study proposes a novel MI p...

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Veröffentlicht in:Comput Intell Neurosci
Hauptverfasser: Liu, Rensong, Zhang, Zhiwen, Duan, Feng, Zhou, Xin, Meng, Zixuan
Format: Artigo
Sprache:Inglês
Veröffentlicht: Hindawi 2017
Schlagworte:
Research Article
Online Zugang:https://ncbi.nlm.nih.gov/pmc/articles/PMC5569879/
https://ncbi.nlm.nih.gov/pubmed/28874909
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1155/2017/2727856
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