Language Model Applications to Spelling with Brain-Computer Interfaces

Sensors

Anderson Mora-Cortes¹  Nikolay V. Manyakov²  Nikolay Chumerin² 

[1] Laboratorium voor Neuro- en Psychofysiologie, KU Leuven, Campus Gasthuisberg, O&N2, Herestraat 49, Leuven B-3000, Belgium;

关键词: Ambient Assisted Living;    Brain-Computer Interfaces;    spelling systems;    electroencephalography;    communication systems;    language models;   

DOI  :  10.3390/s140405967

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.