Literature DB >> 7730759

The EMG-force relationship of the cat soleus muscle and its association with contractile conditions during locomotion.

A C Guimaraes1, W Herzog, T L Allinger, Y T Zhang.   

Abstract

The relationship between force and electromyographic (EMG) signals of the cat soleus muscle was obtained for three animals during locomotion at five different speeds (154 steps), using implanted EMG electrodes and a force transducer. Experimentally obtained force-IEMG (= integrated EMG) relationships were compared with theoretically predicted instantaneous activation levels calculated by dividing the measured force by the predicted maximal force that the muscle could possibly generate as a function of its instantaneous contractile conditions. In addition, muscular forces were estimated from the corresponding EMG records exclusively using an adaptive filtering approach. Mean force-IEMG relationships were highly non-linear but similar in shape for different cats and different speeds of locomotion. The theoretically predicted activation-time plots typically showed two peaks, as did the IEMG-time plots. The first IEMG peak tended to be higher than the second one and it appeared to be associated with the initial priming of the muscle for force production at paw contact and the peak force observed early during the stance phase. The second IEMG peak appeared to be a burst of high muscle activation, which might have compensated for the levels of muscle length and shortening velocity that were suboptimal during the latter part of the stance phase. Although it was difficult to explain the soleus forces on the basis of the theoretically predicted instantaneous activation levels, it was straightforward to approximate these forces accurately from EMG data using an adaptive filtering approach.

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Mesh:

Year:  1995        PMID: 7730759     DOI: 10.1242/jeb.198.4.975

Source DB:  PubMed          Journal:  J Exp Biol        ISSN: 0022-0949            Impact factor:   3.312


  8 in total

1.  Premature deactivation of soleus during the propulsive phase of cat jumping.

Authors:  Motoshi Kaya; Tim R Leonard; Walter Herzog
Journal:  J R Soc Interface       Date:  2008-04-06       Impact factor: 4.118

2.  Interpreting muscle function from EMG: lessons learned from direct measurements of muscle force.

Authors:  Thomas J Roberts; Annette M Gabaldón
Journal:  Integr Comp Biol       Date:  2008-06-18       Impact factor: 3.326

3.  Modifying motor unit territory placement in the Fuglevand model.

Authors:  Jason W Robertson; Jamie A Johnston
Journal:  Med Biol Eng Comput       Date:  2017-04-08       Impact factor: 2.602

4.  How muscle fiber lengths and velocities affect muscle force generation as humans walk and run at different speeds.

Authors:  Edith M Arnold; Samuel R Hamner; Ajay Seth; Matthew Millard; Scott L Delp
Journal:  J Exp Biol       Date:  2013-03-07       Impact factor: 3.312

5.  Vastus lateralis maximum force-generating potential occurs at optimal fascicle length regardless of activation level.

Authors:  Heiliane de Brito Fontana; Walter Herzog
Journal:  Eur J Appl Physiol       Date:  2016-05-10       Impact factor: 3.078

6.  Comparison of regression models for estimation of isometric wrist joint torques using surface electromyography.

Authors:  Amirreza Ziai; Carlo Menon
Journal:  J Neuroeng Rehabil       Date:  2011-09-26       Impact factor: 4.262

7.  Human Leg Model Predicts Muscle Forces, States, and Energetics during Walking.

Authors:  Jared Markowitz; Hugh Herr
Journal:  PLoS Comput Biol       Date:  2016-05-13       Impact factor: 4.475

8.  Relationship of EMG/SMG features and muscle strength level: an exploratory study on tibialis anterior muscles during plantar-flexion among hemiplegia patients.

Authors:  Huihui Li; Guoru Zhao; Yongjin Zhou; Xin Chen; Zhen Ji; Lei Wang
Journal:  Biomed Eng Online       Date:  2014-01-27       Impact factor: 2.819

  8 in total

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