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 (https://doi.org/10.3390/s19061423)

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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.

ORCID iDs

Padfield, Natasha, Zabalza, Jaime ORCID logoORCID: https://orcid.org/0000-0002-0634-1725, Zhao, Huimin, Vargas, Valentin Masero and Ren, Jinchang ORCID logoORCID: https://orcid.org/0000-0001-6116-3194;
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