Automated seizure detection using a self-organizing neural network.

An algorithm for automated seizure detection using the self-organizing map (SOM) neural network (NN), with unsupervised training, was used to detect seizures in 24 long-term EEG recordings. The detection paradigm was tested on a constant 8 channel subset of 18 channel scalp EEG recordings. The NN was trained to recognize seizures using 98 training examples.