Neural Interfacing with Keyboard Output

Brains produce signals in response to motor functions. These signals can be read using a Brain Computer Interface (BCI), such as the Emotiv EPOC. The EPOC uses a set of fourteen electrodes which make contact with the skull at various locations, producing a series of corresponding signals. These signals are unique to an individual based on the action performed. As a result, these signals can be classified for comparison to new signals. The goal of this project is to map incoming signals to emulate a keyboard output. Using OpenViBE software and MATLAB scripting, this project uses machine learning algorithms to classify unique patterns in brainwaves. These patterns are compared to incoming signals and associated with various keyboard commands. Users have the ability to assign their signals to keyboard outputs used to drive a simple program. This project has the potential to increase keyboard usability among people with impaired motor capabilities.