Genetic programming for epileptic pattern recognition in electroencephalographic signals

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@Article{Lopes:2007:ASC,

• author = "Heitor S. Lopes",
• title = "Genetic programming for epileptic pattern recognition in electroencephalographic signals",
• journal = "Applied Soft Computing",
• year = "2007",
• volume = "7",
• number = "1",
• pages = "343--352",
• month = jan,
• keywords = "genetic algorithms, genetic programming, Pattern recognition, Epilepsy, EEG",
• DOI = "doi:10.1016/j.asoc.2005.07.004",
• size = "10 pages",
• abstract = "the genetic programming paradigm, in conjunction with pattern recognition principles, can be used to evolve classifiers capable of recognising epileptic patterns in human electroencephalographic signals. The procedure for feature extraction from the raw signal is detailed, as well as the genetic programming system that properly selects the features and evolves the classifiers. Based on the data sets used, two different epileptic patterns were detected: 3 Hz spike-and-slow-wave-complex (SASWC) and spike-or-sharp-wave (SOSW). After training, classifiers for both patterns were tested with unseen instances, and achieved sensibility = 1.00 and specificity = 0.93 for SASWC patterns, and sensibility = 0.94 and specificity = 0.89 for SOSW patterns. Results are very promising and suggest that the methodology presented can be applied to other pattern recognition tasks in complex signals.",

}

Genetic Programming entries for Heitor Silverio Lopes

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