Estimation of Joint Torque for a Myoelectric Arm by Genetic Programming Based on EMG Signals

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Kiguchi:2012:WAC,
  author =       "Kazuo Kiguchi and Yoshiaki Hayashi",
  booktitle =    "World Automation Congress (WAC 2012)",
  title =        "Estimation of Joint Torque for a Myoelectric Arm by
                 Genetic Programming Based on EMG Signals",
  year =         "2012",
  address =      "Puerto Vallarta, Mexico",
  month =        "24-28 " # jun,
  isbn13 =       "978-1-4673-4497-5",
  URL =          "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6321048",
  keywords =     "genetic algorithms, genetic programming, formatting,
                 insert, style, styling",
  ISSN =         "2154-4824",
  size =         "4 pages",
  abstract =     "An electromyogram (EMG) is an electric signal
                 generated when a muscle is activated. EMG signals can
                 be used as input signals to control a myoelectric arm,
                 a power-assist robot, and so on because EMG signals are
                 generated before a motion. Although many kinds of
                 control methods using EMG signals for a myoelectric arm
                 or a power-assist robot have been proposed, the
                 comparison between the methods is difficult because it
                 is different what each method calculates from a
                 measured signal, and it is not easy to define the best
                 method. In this paper, a myoelectric arm is controlled
                 based on EMG signals as an example of a system in which
                 EMG signals are used as input signals. Genetic
                 programming (GP) is used in order to construct an
                 algorithm for a control method of a myoelectric arm.",
  notes =        "Also known as \cite{6321048}",
}

Genetic Programming entries for Kazuo Kiguchi Yoshiaki Hayashi

Citations