Genetic reasoning for finger sign identification based on forearm electromyogram

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@InProceedings{Tsujimura:2014:AE,
  author =       "Takeshi Tsujimura and Takahiro Hashimoto and 
                 Kiyotaka Izumi",
  booktitle =    "International Conference on Applied Electronics (AE
                 2014)",
  title =        "Genetic reasoning for finger sign identification based
                 on forearm electromyogram",
  year =         "2014",
  month =        sep,
  pages =        "297--302",
  abstract =     "This paper proposes a meta-heuristic data-clustering
                 application to identify finger signs only by measuring
                 surface electromyogram (EMG) of a forearm. It
                 classifies EMG signal patterns peculiar to finger
                 signs. Genetic programming learns intensity
                 characteristics of EMG signals, and creates
                 classification algorithm. Three typical finger signs
                 are evaluated in terms of generated EMG. Experiments
                 are conducted to reveal the successful identification
                 of finger signs in real time.",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/AE.2014.7011724",
  ISSN =         "1803-7232",
  notes =        "Department of Mechanical Engineering, Saga University,
                 840-8502 Japan

                 Also known as \cite{7011724}",
}

Genetic Programming entries for Takeshi Tsujimura Takahiro Hashimoto Kiyotaka Izumi

Citations