A neuro-fuzzy system to support in the diagnostic of epileptic events and non-epileptic events using different fuzzy arithmetical operations

• Autor(a) principal: Carvalho,Lucimar M.F. de
• Data de Publicação: 2008
• Outros Autores: Nassar,Silvia Modesto, Azevedo,Fernando Mendes de, Carvalho,Hugo José Teixeira de, Monteiro,Lucas Lese, Rech,Ciciliana M. Zílio
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Arquivos de neuro-psiquiatria (Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0004-282X2008000200007
• topic: epileptic events; non epileptic events; artificial neural network; fuzzy logic

OBJECTIVE: To investigate different fuzzy arithmetical operations to support in the diagnostic of epileptic events and non epileptic events. METHOD: A neuro-fuzzy system was developed using the NEFCLASS (NEuro Fuzzy CLASSIfication) architecture and an artificial neural network with backpropagation learning algorithm (ANNB). RESULTS: The study was composed by 244 patients with a bigger frequency of the feminine sex. The number of right decisions at the test phase, obtained by the NEFCLASS and ANNB was 83.60% and 90.16%, respectively. The best sensibility result was attained by NEFCLASS (84.90%); the best specificity result were attained by ANNB with 95.65%. CONCLUSION: The proposed neuro-fuzzy system combined the artificial neural network capabilities in the pattern classifications together with the fuzzy logic qualitative approach, leading to a bigger rate of system success.