Neural network for epileptic activity detection is designed to analyze signals from the electroencephalogram (EEG) and to gain additional information about the signals thus enabling a more accurate diagnosis. The main function of the module is to identify epileptic activity in the signals of the EEG. To implement this function specially developed algorithms which are based on neural network theory and chaos theory are employed. These algorithms has allowed to develop a complex system aimed at an effective detection of epileptic activity of different shapes and durations, without extra pre-training of the system.

• Regional Hospital Brest, Healthcare Institution, Belarus