Estimation of joint torque for a myoelectric arm by genetic programming based on EMG signals

Kazuo Kiguchi, Yoshiaki Hayashi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

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.

Original languageEnglish
Title of host publication2012 World Automation Congress, WAC 2012
Publication statusPublished - Dec 14 2012
Event2012 World Automation Congress, WAC 2012 - Puerto Vallarta, Mexico
Duration: Jun 24 2012Jun 28 2012

Publication series

NameWorld Automation Congress Proceedings
ISSN (Print)2154-4824
ISSN (Electronic)2154-4832

Other

Other2012 World Automation Congress, WAC 2012
CountryMexico
CityPuerto Vallarta
Period6/24/126/28/12

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All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering

Cite this

Kiguchi, K., & Hayashi, Y. (2012). Estimation of joint torque for a myoelectric arm by genetic programming based on EMG signals. In 2012 World Automation Congress, WAC 2012 [6321048] (World Automation Congress Proceedings).