Patient independent Spike-Wave Complex Detection in EEG Signals with an Artificial Neural Network

Abstract

Spike-Wave Complexes in EEG signals may occur randomly in recordings of epileptic patients. Neurologists can recognize these complexes, which differ a lot from patient to patient. Automated Spike-Wave Complex detection systems have problems with these differences. Some of these systems are rule-based, others use features extracted from examples of Spike-Wave Complexes and normal EEG for detection. A detection system is proposed that uses examples of Spike-Wave Complexes as indicated by a neurologist. A neural network extracts a set of representative Spike-Wave Complexes, which are used for detection. The set of examples can be adapted to the neurologists to provide a user-adaptable detection system. Keywords--- Medical signal processing, pattern recognition, neural networks. I. Introduction The ElectroEncephaloGram (EEG) is a recording of the electrical activity of the brain. If the EEG is analyzed by frequency, four basic waves can be distinguished, alpha, beta, theta and delta wav..