Title :
Detection of epileptic events using genetic programming
Author :
Marchesi, Bruno ; Stelle, Álvaro Luiz ; Lopes, Heitor Silvério
Author_Institution :
Parana Fed. Center for Technol. Educ., Curitiba, Brazil
fDate :
30 Oct-2 Nov 1997
Abstract :
This paper presents a method using genetic programming for automatic detection of 3 Hz spike-and-slow-wave complexes, that are a characteristic of typical absences, in electroencephalogram (EEG) signals. Training features are extracted from 1s EEG frames, randomly chosen from pre-recorded files. The frames are visually classified as spike-and-slow-wave complexes (SASWC) or non-spike-and-slow-wave complexes (NSASWC). Genetic programming techniques are then applied to these data to build a program capable of recognizing such complexes
Keywords :
electroencephalography; evolutionary computation; learning (artificial intelligence); medical expert systems; medical signal processing; pattern classification; 3 Hz; Darwinian survival and reproduction; EEG signals; automatic detection; complexes recognition; epileptic events detection; genetic algorithm; genetic programming; ictal period; pattern recognition; spike-and-slow-wave complexes; training features; typical absences; visually classified frames; Automatic programming; Data mining; Diseases; Electroencephalography; Epilepsy; Event detection; Feature extraction; Genetic algorithms; Genetic programming; Signal processing;
Conference_Titel :
Engineering in Medicine and Biology Society, 1997. Proceedings of the 19th Annual International Conference of the IEEE
Conference_Location :
Chicago, IL
Print_ISBN :
0-7803-4262-3
DOI :
10.1109/IEMBS.1997.756577
