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

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@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