Decomposition of EMG patterns as combinations of time-varying muscle synergies

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


A key issue in the study of the neural control of movement is understanding how the CNS coordinates the large number degrees of freedom of the musculoskeletal system to achieve a variety of behavioral goals. The organization of muscle synergies, i.e. groups of muscles controlled as units, might simplify this problem by reducing the dimensionality of the control space. We propose a model for the generation of muscle patterns as linear combinations of synergies with a specific spatiotemporal structure. We introduce an algorithm to extract multiple instances of time-varying muscle synergies from EMG patterns of arbitrary length. Simulation shows that the algorithm is capable of recovering a set of synergies from the data constructed by their combinations. We use this algorithm to decompose the EMG patterns recorded during swimming in an intact, unrestrained frog as combinations of three synergies. The recruitment of different synergies over time and episodes appears to capture the characteristic of the corresponding behavior. These results suggest that this approach can provide new insight into the mechanism of biological motor control.

Original languageEnglish
Title of host publicationInternational IEEE/EMBS Conference on Neural Engineering, NER
PublisherIEEE Computer Society
Number of pages4
ISBN (Print)0780375793
Publication statusPublished - 2003
Event1st International IEEE EMBS Conference on Neural Engineering - Capri Island, Italy
Duration: Mar 20 2003Mar 22 2003


Other1st International IEEE EMBS Conference on Neural Engineering
CityCapri Island


  • Control systems
  • Electromyography
  • Humans
  • Iterative algorithms
  • Muscles
  • Musculoskeletal system
  • Physiology
  • Recruitment
  • Spatiotemporal phenomena
  • Time varying systems

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering


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