Making waves useful: Improving epileptiform activity recognition using energy criteria

The existing programming tools do not combine the attributes of easy to use and affordability. The existing procedures for spike detection consist mostly of sequences of tasks such as manual data preparation, followed by the use of multiple software packages (for example, from a commercial EEG recording program into MATLAB). The programming tool presented was developed to overcome these two major disadvantages. The system performs high-resolution external recordings of electroencephalographic (EEG) activity. The research goal was to propose an epileptiform activity (EFA) detection method that combines traditional task with energy criteria. The method uses EFA descriptors based on EEG recordings to produce formulas that can be applied for fast and automated EFA detection. An easy to use programming package was developed to demonstrate the proposed method.