An ERP-based brain-computer interface for text entry using rapid serial visual presentation and language modeling

Authors:
K. E. Hild;U. Orhan;D. Erdogmus;B. Roark;B. Oken;S. Purwar;H. Nezamfar;M. Fried-Oken
Affiliations:
Oregon Health and Science University;Northeastern University;Northeastern University;Oregon Health and Science University;Oregon Health and Science University;Northeastern University;Northeastern University;Oregon Health and Science University
Venue:
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: Systems Demonstrations
Year:
2011

Citing 2
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Scanning methods and language modeling for binary switch typing

SLPAT '10 Proceedings of the NAACL HLT 2010 Workshop on Speech and Language Processing for Assistive Technologies

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Abstract

Event related potentials (ERP) corresponding to stimuli in electroencephalography (EEG) can be used to detect the intent of a person for brain computer interfaces (BCI). This paradigm is widely used to build letter-by-letter text input systems using BCI. Nevertheless using a BCI-typewriter depending only on EEG responses will not be sufficiently accurate for single-trial operation in general, and existing systems utilize many-trial schemes to achieve accuracy at the cost of speed. Hence incorporation of a language model based prior or additional evidence is vital to improve accuracy and speed. In this demonstration we will present a BCI system for typing that integrates a stochastic language model with ERP classification to achieve speedups, via the rapid serial visual presentation (RSVP) paradigm.