EEG-based Communication with a Predictive Text Algorithm
This work addresses communication challenges for individuals with severe disabilities, though it is incremental as it builds on existing EEG and predictive text methods.
The paper tackled the problem of enabling communication for people with severe speech and muscular disabilities by developing an EEG-based system that detects voluntary eye blinks to trigger text input, with results indicating effective application in facilitating speech.
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.