Robot motion governing using upper limb EMG signal based on empirical mode decomposition

Hsiu Jen Liu*, Kuu-Young Young

*Corresponding author for this work

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

4 Scopus citations

Abstract

This paper presents a simple and effective approach to govern robot arm motion in real time using upper limb EMG signals. Considering the non-stationary and nonlinear characteristics of the EMG signals, in the design for feature extraction, we introduce the empirical mode decomposition (EMD) to decompose the EMG signals into intrinsic mode functions (IMFs). Each IMF represents different physical characteristic, so that the muscular movement can be recognized. We then integrate it with a so-called initial point detection method previously proposed to establish the mapping between the upper limb EMG signals and corresponding robot arm movements in real time. In addition, for each individual user, we adopt a fuzzy approach to select proper system parameters for motion classification. The experimental results show the feasibility of the proposed approach with accurate motion recognition.

Original languageEnglish
Title of host publication2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010
Pages441-446
Number of pages6
DOIs
StatePublished - 1 Dec 2010
Event2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010 - Istanbul, Turkey
Duration: 10 Oct 201013 Oct 2010

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
ISSN (Print)1062-922X

Conference

Conference2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010
CountryTurkey
CityIstanbul
Period10/10/1013/10/10

Keywords

  • Electromyography (EMG)
  • Empirical mode decomposition
  • Robot control
  • Upper limb motion classification

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    Liu, H. J., & Young, K-Y. (2010). Robot motion governing using upper limb EMG signal based on empirical mode decomposition. In 2010 IEEE International Conference on Systems, Man and Cybernetics, SMC 2010 (pp. 441-446). [5641770] (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics). https://doi.org/10.1109/ICSMC.2010.5641770