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

Citations