APPROACH TO SYNERGY ANALYSIS OF EMG IN GAIT.

Jia-Jin Chen, R. G. Shiavi

Research output: Contribution to conferencePaper

Abstract

The implementation of an electromyographic (EMG) synergy analysis assistant system that is based on membership function and heuristic reasoning is discussed. Results obtained from clustering analysis of mixed database have shown that for single muscle there is no crisp boundary between normal and pathological patterns. However, the distribution among clusters of pathological data is different from the normal one. The synergy analysis assistant provides important information for the diagnostic application of the EMG linear envelope; the grades of membership reflect the ordering of one EMG pattern in the templates that are defined by the averaged profiles from clustering analysis. The advantages of the fuzzy reasoning scheme are its ability to represent uncertainty and its ability to propagate evidence in the decision process.

Original languageEnglish
Pages1988-1989
Number of pages2
Publication statusPublished - 1987 Dec 1

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Membership functions
Muscle
Uncertainty

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Chen, J-J., & Shiavi, R. G. (1987). APPROACH TO SYNERGY ANALYSIS OF EMG IN GAIT.. 1988-1989.
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Chen, J-J & Shiavi, RG 1987, 'APPROACH TO SYNERGY ANALYSIS OF EMG IN GAIT.', pp. 1988-1989.

APPROACH TO SYNERGY ANALYSIS OF EMG IN GAIT. / Chen, Jia-Jin; Shiavi, R. G.

1987. 1988-1989.

Research output: Contribution to conferencePaper

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