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EEG-Based Brain-Computer Interfaces Using Motor-Imagery: Techniques and Challenges

2019; Multidisciplinary Digital Publishing Institute; Volume: 19; Issue: 6 Linguagem: Inglês

10.3390/s19061423

1424-8220

Natasha Padfield, Jaime Zabalza, Huimin Zhao, Valentín Masero, Jinchang Ren,

Advanced Memory and Neural Computing

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.