Force-firing rate relation of neural network model for muscle force control

Takanori Uchiyama, Kenzo Akazawa

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

Abstract

A neural network model for muscle force control was constructed. It contained single motor cortex output cell, actual number of α motoneurons, Renshaw cells and muscle unit. The relation between muscle force and firing rate of α motoneurons of the model was investigated. The relation depended on the absolute refractory time of α motoneurons, RIPSP by Renshaw cells and firing pattern of Renshaw cells. The model showed the force-firing rate relation which was almost similar to that observed in human skeletal muscle.

Original languageEnglish
Title of host publicationAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
PublisherIEEE
Number of pages1
ISBN (Print)0780356756
Publication statusPublished - 1999 Dec 1
EventProceedings of the 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Fall Meeting of the Biomedical Engineering Society (1st Joint BMES / EMBS) - Atlanta, GA, USA
Duration: 1999 Oct 131999 Oct 16

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume1
ISSN (Print)0589-1019

Other

OtherProceedings of the 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Fall Meeting of the Biomedical Engineering Society (1st Joint BMES / EMBS)
CityAtlanta, GA, USA
Period99/10/1399/10/16

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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  • Cite this

    Uchiyama, T., & Akazawa, K. (1999). Force-firing rate relation of neural network model for muscle force control. In Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings (Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings; Vol. 1). IEEE.