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Using Multiple Decomposition Methods and Cluster Analysis to Find and Categorize Typical Patterns of EEG Activity in Motor Imagery Brain-Computer Interface Experiments.

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第一作者： Alexander,Frolov

第一单位： Research Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia.;Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Science, Moscow, Russia.

作者： Alexander,Frolov ^[1] ; Pavel,Bobrov ^[1] ; Elena,Biryukova ^[1] ; Mikhail,Isaev ^[1] ; Yaroslav,Kerechanin ^[1] ; Dmitry,Bobrov ^[2] ; Alexander,Lekin ^[2]

作者单位： Research Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia.;Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Science, Moscow, Russia. ^[1] Research Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia. ^[2]

关键词 EEG pattern extraction blind source separation brain–computer interface cluster analysis common spatial patterns independent component analysis motor imagery

DOI 10.3389/frobt.2020.00088

PMID 33501255

发布时间 2021-01-29

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Using Multiple Decomposition Methods and Cluster Analysis to Find and Categorize Typical Patterns of EEG Activity in Motor Imagery Brain-Computer Interface Experiments.

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Using Multiple Decomposition Methods and Cluster Analysis to Find and Categorize Typical Patterns of EEG Activity in Motor Imagery Brain-Computer Interface Experiments.

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