Estimation of muscle synergies in the presence of arbitrary inputs

Vengateswaran J. Ravichandran*, Eric Perreault

*Corresponding author for this work

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

1 Scopus citations

Abstract

The strategy the central nervous system utilizes to produce movements in the face of multiple degrees of freedom available has been a subject of study for the past few years. Of the possible mechanisms, the muscle synergies - stereotypical coordinated patterns of muscle activity elicited by dedicated networks have been suggested to be the building blocks. Based on this hypothesis, several algorithms have been proposed to discern these synergies from the recorded electromyographic signals (EMG). In the proposed model, the synergies are treated as filters (IRFs) that take as input any arbitrary non-negative signal. That is, the EMG is seen as a convolution mixture of synergies and corresponding inputs.

Original languageEnglish (US)
Title of host publicationProceedings of the 2005 IEEE 9th International Conference on Rehabilitation Robotics, ICORR 2005
Pages33-36
Number of pages4
DOIs
StatePublished - Dec 1 2005
Event2005 IEEE 9th International Conference on Rehabilitation Robotics, ICORR 2005 - Chicago, IL, United States
Duration: Jun 28 2005Jul 1 2005

Publication series

NameProceedings of the 2005 IEEE 9th International Conference on Rehabilitation Robotics
Volume2005

Other

Other2005 IEEE 9th International Conference on Rehabilitation Robotics, ICORR 2005
Country/TerritoryUnited States
CityChicago, IL
Period6/28/057/1/05

ASJC Scopus subject areas

  • Engineering(all)

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