A Novel Combination of Natural Language Processing and Brain Computer Interface in a Communication System
Year: 2019
Type: dissertation
Abstract: A brain-computer interface (BCI) is a communication system that enables individuals with severe physical disabilities to communicate or control external devices through their brain activities. In this study, we proposed a communication system combining natural language processing (NLP) and BCI in a question and answer paradigm. Specifically, we combined a context-aware predictive speller and an answer generation engine that comprehends the question being asked of the user, to efficiently present potential conversational responses. The user could either type a response or select from suggested answers. If the user started typing, the cells containing suggestions were repopulated with context-relevant words matching the user’s typed characters, thereby reducing typing time. We have evaluated our proposed system through 4 sessions per subject in terms of accuracy, bit rate, timing, and user satisfaction. Our data analysis has validated that the proposed paradigm doubles the typing speed, increases accuracy and reduces mental demand of message composition.
Source: TSpace (University of Toronto)
Author: Maryam Fallah
Language: English
Subfield: Cognitive Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W3014392277