EEG-based brain-computer interfaces using motor-imagery : techniques and challenges

Padfield, Natasha and Zabalza, Jaime and Zhao, Huimin and Vargas, Valentin Masero and Ren, Jinchang (2019) EEG-based brain-computer interfaces using motor-imagery : techniques and challenges. Sensors, 19 (6). 1423. ISSN 1424-8220

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    Abstract

    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.

    Author(s):Padfield, Natasha, Zabalza, Jaime, Zhao, Huimin, Vargas, Valentin Masero and Ren, Jinchang ORCID logoORCID: https://orcid.org/0000-0001-6116-3194
    Item type:Article
    ID code:67409
    Keywords:brain-computer interfaces, electroencephalography, motor-imagery, Electrical engineering. Electronics Nuclear engineering, Electrical and Electronic Engineering
    Subjects:Technology > Electrical engineering. Electronics Nuclear engineering
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    Technology and Innovation Centre > Sensors and Asset Management
    Depositing user: Pure Administrator
    Date deposited:22 Mar 2019 13:56
    Last modified:15 Nov 2019 03:10
    Related URLs:
    URI:https://strathprints.strath.ac.uk/id/eprint/67409
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