{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T00:22:57Z","timestamp":1785370977097,"version":"3.55.0"},"reference-count":188,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2019,3,22]],"date-time":"2019-03-22T00:00:00Z","timestamp":1553212800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/s19061423","type":"journal-article","created":{"date-parts":[[2019,3,25]],"date-time":"2019-03-25T06:56:52Z","timestamp":1553497012000},"page":"1423","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":536,"title":["EEG-Based Brain-Computer Interfaces Using Motor-Imagery: Techniques and Challenges"],"prefix":"10.3390","volume":"19","author":[{"given":"Natasha","family":"Padfield","sequence":"first","affiliation":[{"name":"Centre for Signal and Image Processing, University of Strathclyde, Glasgow G1 1XW, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jaime","family":"Zabalza","sequence":"additional","affiliation":[{"name":"Centre for Signal and Image Processing, University of Strathclyde, Glasgow G1 1XW, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huimin","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Computer Sciences, Guangdong Polytechnic Normal University, Guangzhou 510665, China"},{"name":"The Guangzhou Key Laboratory of Digital Content Processing and Security Technologies, Guangzhou 510665, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Valentin","family":"Masero","sequence":"additional","affiliation":[{"name":"Department of Computer Systems and Telematics Engineering, Universidad de Extremadura, 06007 Badajoz, Spain"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6116-3194","authenticated-orcid":false,"given":"Jinchang","family":"Ren","sequence":"additional","affiliation":[{"name":"Centre for Signal and Image Processing, University of Strathclyde, Glasgow G1 1XW, UK"},{"name":"School of Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan 030024, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,3,22]]},"reference":[{"key":"ref_1","unstructured":"Soegaard, M., and Dam, R.F. 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