Several changes occur in the brain in response to voluntary and involuntary activities performed by a person. The ability to retrieve data from the brain within a time space provides a basis for in-depth analyses that offer insight on what changes occur in the brain during its decision-making processes. In this work, we present the technical description and software implementation of an electroencephalographic (EEG) based communication system. We read EEG data in real-time with which we compute the likelihood that a voluntary eye blink has been made by a person and use the decision to trigger buttons on a user interface in order to produce text. Relevant texts are suggested using a modification of the T9 algorithm. Our results indicate that EEG-based technology can be effectively applied in facilitating speech for people with severe speech and muscular disabilities, providing a foundation for future work in the area.
@article{arxiv.1812.05945,
title = {EEG-based Communication with a Predictive Text Algorithm},
author = {Daniel Omeiza and Kayode Sakariyah Adewole and Daniel Nkemelu},
journal= {arXiv preprint arXiv:1812.05945},
year = {2020}
}