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

Natasha Padfield, Jaime Zabalza, Huimin Zhao, Valentin Masero Vargas, Jinchang Ren

Research output: Contribution to journalReview articlepeer-review

113 Citations (Scopus)
45 Downloads (Pure)


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.
Original languageEnglish
Article number1423
Number of pages36
Issue number6
Publication statusPublished - 22 Mar 2019


  • brain-computer interfaces
  • electroencephalography
  • motor-imagery


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