Journal
SENSORS
Volume 19, Issue 6, Pages -Publisher
MDPI
DOI: 10.3390/s19061423
Keywords
brain-computer interface (BCI); electroencephalography (EEG); motor-imagery (MI)
Funding
- University of Strathclyde
- National Natural Science Foundation of China [61672008]
- Guangdong Provincial Application-oriented Technical Research and Development Special fund project [2016B010127006]
- Scientific and Technological Projects of Guangdong Province [2017A050501039]
- Guangdong Key Laboratory of Intellectual Property Big Data of China [2018B030322016]
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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.
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