Novel Methods for EEG Visualization and Visualization

David Slayback, Syed Abdali, Justin Brooks, W. David Hairston, Paul Groves

Abstract: Here we present several methods for representing electroencephalography (EEG) signals in a manner that is intuitive to non-scientists, in order to improve communication about the meaning of the underlying recorded signal. To support the use of various forms of EEG signal, we have developed a signal processing pipeline to filter noise and extract relevant, user-selected features. We provide two forms of presentation: a virtual reality (VR) system with a spatial audio and visualization, and a physical head model capable of displaying location and frequency-specific data. Examples are given for applications of the full system.