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EEG-Based Brain-Computer Interfaces Using Motor-Imagery: Techniques and Challenges
by
Zhao, Huimin
, Padfield, Natasha
, Ren, Jinchang
, Zabalza, Jaime
, Masero, Valentin
in
Brain - physiology
/ brain-computer interface (BCI)
/ Brain-Computer Interfaces
/ electroencephalography (EEG)
/ Electroencephalography - methods
/ Evoked Potentials
/ Humans
/ motor-imagery (MI)
/ Principal Component Analysis
/ Review
/ Signal Processing, Computer-Assisted
2019
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EEG-Based Brain-Computer Interfaces Using Motor-Imagery: Techniques and Challenges
by
Zhao, Huimin
, Padfield, Natasha
, Ren, Jinchang
, Zabalza, Jaime
, Masero, Valentin
in
Brain - physiology
/ brain-computer interface (BCI)
/ Brain-Computer Interfaces
/ electroencephalography (EEG)
/ Electroencephalography - methods
/ Evoked Potentials
/ Humans
/ motor-imagery (MI)
/ Principal Component Analysis
/ Review
/ Signal Processing, Computer-Assisted
2019
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Do you wish to request the book?
EEG-Based Brain-Computer Interfaces Using Motor-Imagery: Techniques and Challenges
by
Zhao, Huimin
, Padfield, Natasha
, Ren, Jinchang
, Zabalza, Jaime
, Masero, Valentin
in
Brain - physiology
/ brain-computer interface (BCI)
/ Brain-Computer Interfaces
/ electroencephalography (EEG)
/ Electroencephalography - methods
/ Evoked Potentials
/ Humans
/ motor-imagery (MI)
/ Principal Component Analysis
/ Review
/ Signal Processing, Computer-Assisted
2019
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EEG-Based Brain-Computer Interfaces Using Motor-Imagery: Techniques and Challenges
Journal Article
EEG-Based Brain-Computer Interfaces Using Motor-Imagery: Techniques and Challenges
2019
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Overview
Electroencephalography (EEG)-based brain-computer interfaces (BCIs), particularly those using motor-imagery (MI) data, have the potential to become groundbreaking technologies in both clinical and entertainment settings. MI data is generated when a subject imagines the movement of a limb. This paper reviews state-of-the-art signal processing techniques for MI EEG-based BCIs, with a particular focus on the feature extraction, feature selection and classification techniques used. It also summarizes the main applications of EEG-based BCIs, particularly those based on MI data, and finally presents a detailed discussion of the most prevalent challenges impeding the development and commercialization of EEG-based BCIs.
Publisher
MDPI,MDPI AG
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