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.
Creators(s): |
Padfield, Natasha, Zabalza, Jaime ![]() ![]() | Item type: | Article |
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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: | 22 Jan 2021 03:59 |
Related URLs: | |
URI: | https://strathprints.strath.ac.uk/id/eprint/67409 |
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