{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,21]],"date-time":"2026-02-21T18:52:19Z","timestamp":1771699939005,"version":"3.50.1"},"reference-count":125,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2014,3,26]],"date-time":"2014-03-26T00:00:00Z","timestamp":1395792000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Within the Ambient Assisted Living (AAL) community, Brain-Computer Interfaces (BCIs) have raised great hopes as they provide alternative communication means for persons with disabilities bypassing the need for speech and other motor activities. Although significant advancements have been realized in the last decade, applications of language models (e.g., word prediction, completion) have only recently started to appear in BCI systems. The main goal of this article is to review the language model applications that supplement non-invasive BCI-based communication systems by discussing their potential and limitations, and to discern future trends. First, a brief overview of the most prominent BCI spelling systems is given, followed by an in-depth discussion of the language models applied to them. These language models are classified according to their functionality in the context of BCI-based spelling: the static\/dynamic nature of the user interface, the use of error correction and predictive spelling, and the potential to improve their classification performance by using language models. To conclude, the review offers an overview of  the advantages and challenges when implementing language models in BCI-based communication systems when implemented in conjunction with other AAL technologies.<\/jats:p>","DOI":"10.3390\/s140405967","type":"journal-article","created":{"date-parts":[[2014,3,26]],"date-time":"2014-03-26T11:20:33Z","timestamp":1395832833000},"page":"5967-5993","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":37,"title":["Language Model Applications to Spelling with  Brain-Computer Interfaces"],"prefix":"10.3390","volume":"14","author":[{"given":"Anderson","family":"Mora-Cortes","sequence":"first","affiliation":[{"name":"Laboratorium voor Neuro- en Psychofysiologie, KU Leuven, Campus Gasthuisberg, O&N2,  Herestraat 49, Leuven B-3000, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nikolay","family":"Manyakov","sequence":"additional","affiliation":[{"name":"Laboratorium voor Neuro- en Psychofysiologie, KU Leuven, Campus Gasthuisberg, O&N2,  Herestraat 49, Leuven B-3000, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nikolay","family":"Chumerin","sequence":"additional","affiliation":[{"name":"Laboratorium voor Neuro- en Psychofysiologie, KU Leuven, Campus Gasthuisberg, O&N2,  Herestraat 49, Leuven B-3000, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marc","family":"Van Hulle","sequence":"additional","affiliation":[{"name":"Laboratorium voor Neuro- en Psychofysiologie, KU Leuven, Campus Gasthuisberg, O&N2,  Herestraat 49, Leuven B-3000, Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2014,3,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1109\/TNSRE.2003.814448","article-title":"ERPs evoked by different matrix sizes: Implications for a brain computer interface (BCI) system","volume":"11","author":"Allison","year":"2003","journal-title":"IEEE Trans. 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