Literature DB >> 15201310

Factors governing the form of the relation between muscle force and the EMG: a simulation study.

Ping Zhou1, William Zev Rymer.   

Abstract

The dependence of the form of the EMG-force relation on key motoneuron and muscle properties was explored using a simulation approach. Surface EMG signals and isometric forces were simulated using existing motoneuron pool, muscle force, and surface EMG models, based primarily on reported properties of the first dorsal interosseous (FDI) muscle in humans. Our simulation results indicate that the relation between electrical and mechanical properties of the individual motor unit level plays the dominant role in determining the overall EMG amplitude-force relation of the muscle, while the underlying motor unit firing rate strategy appears to be a less important factor. However, different motor unit firing rate strategies result in substantially different relations between counts of the numbers of motoneuron discharges and the isometric force. Our simulation results also show that EMG amplitude (estimated as the average rectified value) increases as a result of synchronous discharges of different motor units within the pool, but the magnitude of this increase is determined primarily by the action potential duration of the synchronized motor units. Furthermore, when the EMG effects are normalized to their maximum levels, motor unit synchrony does not exert significant effects on the form of the EMG-force relation, provided that the synchrony level is held similar at different excitation levels.

Entities:  

Mesh:

Year:  2004        PMID: 15201310     DOI: 10.1152/jn.00367.2004

Source DB:  PubMed          Journal:  J Neurophysiol        ISSN: 0022-3077            Impact factor:   2.714


  20 in total

1.  Extraction of individual muscle mechanical action from endpoint force.

Authors:  Jason J Kutch; Arthur D Kuo; William Z Rymer
Journal:  J Neurophysiol       Date:  2010-04-14       Impact factor: 2.714

2.  Relationships between surface EMG variables and motor unit firing rates.

Authors:  Anita Christie; J Greig Inglis; Gary Kamen; David A Gabriel
Journal:  Eur J Appl Physiol       Date:  2009-06-21       Impact factor: 3.078

3.  Amplitude cancellation of motor-unit action potentials in the surface electromyogram can be estimated with spike-triggered averaging.

Authors:  Dario Farina; Corrado Cescon; Francesco Negro; Roger M Enoka
Journal:  J Neurophysiol       Date:  2008-05-07       Impact factor: 2.714

4.  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

5.  Neural control of muscle force: indications from a simulation model.

Authors:  Paola Contessa; Carlo J De Luca
Journal:  J Neurophysiol       Date:  2012-12-12       Impact factor: 2.714

6.  When 90% of the variance is not enough: residual EMG from muscle synergy extraction influences task performance.

Authors:  Victor R Barradas; Jason J Kutch; Toshihiro Kawase; Yasuharu Koike; Nicolas Schweighofer
Journal:  J Neurophysiol       Date:  2020-04-08       Impact factor: 2.714

7.  A simulation-based analysis of motor unit number index (MUNIX) technique using motoneuron pool and surface electromyogram models.

Authors:  Xiaoyan Li; William Zev Rymer; Ping Zhou
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2012-04-13       Impact factor: 3.802

8.  EMG-force relation in the first dorsal interosseous muscle of patients with amyotrophic lateral sclerosis.

Authors:  Faezeh Jahanmiri-Nezhad; Xiaogang Hu; Nina L Suresh; William Z Rymer; Ping Zhou
Journal:  NeuroRehabilitation       Date:  2014-01-01       Impact factor: 2.138

9.  Modified motor unit number index: A simulation study of the first dorsal interosseous muscle.

Authors:  Xiaoyan Li; Sanjeev D Nandedkar; Ping Zhou
Journal:  Med Eng Phys       Date:  2015-11-28       Impact factor: 2.242

10.  Recruitment in retractor bulbi muscle during eyeblink conditioning: EMG analysis and common-drive model.

Authors:  N F Lepora; J Porrill; C H Yeo; C Evinger; P Dean
Journal:  J Neurophysiol       Date:  2009-08-12       Impact factor: 2.714

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.