S. Chetty (South Africa) and G.K. Venayagamoorthy (USA)
Neural networks, brain tumours, EEG signals
This paper presents pattern recognition of electroencephalograph (EEG) signals using artificial neural networks (ANNs). The ANN based EEG classifier in this paper distinguishes between the EEG signal of a normal patient and that of a brain tumour patient. A further exercise carried out is a comparison between the different size of input images and their results. Using artificial neural networks, the need for an expert neurologist to analyze EEG signals is eliminated or minimized. This will in turn benefit rural/country areas where there is a shortage of expert doctors for EEG analysis or medical professionals of screening EEG signals for abnormalities under the different noisy conditions in which the EEG signals are captured/analysed. The preliminary results are presented to show that an ANN can classify correctly EEG signals of healthy and brain-tumour patients.
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