{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T04:35:32Z","timestamp":1792125332822,"version":"4.4.0"},"reference-count":117,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T00:00:00Z","timestamp":1753833600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Bioengineering"],"abstract":"<jats:p>Brain\u2013computer interface (BCI) technology holds promise for improving motor rehabilitation in stroke patients. This review explores the immediate and long-term effects of BCI training, shedding light on the potential benefits and challenges. Clinical studies have demonstrated that BCIs yield significant immediate improvements in motor functions following stroke. Patients can engage in BCI training safely, making it a viable option for rehabilitation. Evidence from single-group studies consistently supports the effectiveness of BCIs in enhancing patients\u2019 performance. Despite these promising findings, the evidence regarding long-term effects remains less robust. Further studies are needed to determine whether BCI-induced changes are permanent or only last for short durations. While evaluating the outcomes of BCI, one must consider that different BCI training protocols may influence functional recovery. The characteristics of some of the paradigms that we discuss are motor imagery-based BCIs, movement-attempt-based BCIs, and brain-rhythm-based BCIs. Finally, we examine studies suggesting that integrating BCIs with other devices, such as those used for functional electrical stimulation, has the potential to enhance recovery outcomes. We conclude that, while BCIs offer immediate benefits for stroke rehabilitation, addressing long-term effects and optimizing clinical implementation remain critical areas for further investigation.<\/jats:p>","DOI":"10.3390\/bioengineering12080820","type":"journal-article","created":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T07:37:23Z","timestamp":1753861043000},"page":"820","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":36,"title":["Brain-Computer Interfaces for Stroke Motor Rehabilitation"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-9875-3586","authenticated-orcid":false,"given":"Alessandro","family":"Tonin","sequence":"first","affiliation":[{"name":"Digital Medicine Laboratory, IRCCS San Camillo Hospital, Via Alberoni 70, 30126 Venice, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5504-0251","authenticated-orcid":false,"given":"Marianna","family":"Semprini","sequence":"additional","affiliation":[{"name":"Rehab Technologies Lab, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5990-5734","authenticated-orcid":false,"given":"Pawel","family":"Kiper","sequence":"additional","affiliation":[{"name":"Healthcare Innovation Technology Lab, IRCCS San Camillo Hospital, Via Alberoni 70, 30126 Venice, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6485-5559","authenticated-orcid":false,"given":"Dante","family":"Mantini","sequence":"additional","affiliation":[{"name":"Movement Control and Neuroplasticity Research Group, KU Leuven, Tervuursevest 101, 3001 Leuven, Belgium"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1055\/s-0038-1649503","article-title":"Global Burden of Stroke","volume":"38","author":"Katan","year":"2018","journal-title":"Semin. 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