Literature DB >> 8505346

Muscle coordination of movement: a perspective.

F E Zajac1.   

Abstract

Multijoint movement requires the coordination of many muscles. Because multijoint movement is complex, kinesiological data must be analyzed and interpreted in the context of forward dynamical models rich enough to study coordination; otherwise, principles will remain elusive. The complexity arises because a muscle acts to accelerate all joints and segments, even joints it does not span and segments to which it does not attach. A biarticular muscle can even act to accelerate one of the joints it spans opposite to its anatomical classification. For example, gastrocnemius may act to accelerate the knee into extension during upright standing. One powerful forward dynamical modeling method to study muscle coordination is optimal control theory because simulations of movement can be produced. These simulations can either attempt to replicate experimental data, without hypothesizing the purpose of the motor task, or otherwise generate muscle and movement trajectories that best accomplish the hypothesized task. Application of the theory to the study of maximum-height jumping has provided insight into the biomechanical principles of jumping, such as: (i) jump height is more sensitive to muscle strength than to muscle speed, and insensitive to musculotendon compliance; (ii) uniarticular muscles generate the propulsive energy and biarticular muscles fine-tune the coordination; and (iii) countermovement is often desirable, even in squat jumps, because it seems both to prolong the duration of upwards propulsion, and to give muscles time to develop force so the body can move upwards initially with high acceleration. The effort necessary to develop forward dynamical models has been so high, however, that model-generated data of jumping or any other task are meager. An interactive computer workstation environment is proposed whereby users can develop neuromusculoskeletal control models, generate simulations of motor tasks, and display both kinesiological and modeling data more easily (e.g., animations). By studying a variety of motor tasks well, each within a theoretical framework, hopefully muscle coordination principles will soon emerge.

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Year:  1993        PMID: 8505346     DOI: 10.1016/0021-9290(93)90083-q

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  47 in total

Review 1.  Wheelchair propulsion biomechanics: implications for wheelchair sports.

Authors:  Y Vanlandewijck; D Theisen; D Daly
Journal:  Sports Med       Date:  2001       Impact factor: 11.136

2.  Comprehensive joint feedback control for standing by functional neuromuscular stimulation-a simulation study.

Authors:  Raviraj Nataraj; Musa L Audu; Robert F Kirsch; Ronald J Triolo
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2010-10-04       Impact factor: 3.802

Review 3.  Understanding Vertical Jump Potentiation: A Deterministic Model.

Authors:  Timothy J Suchomel; Hugh S Lamont; Gavin L Moir
Journal:  Sports Med       Date:  2016-06       Impact factor: 11.136

4.  Long-latency muscle activity reflects continuous, delayed sensorimotor feedback of task-level and not joint-level error.

Authors:  Seyed A Safavynia; Lena H Ting
Journal:  J Neurophysiol       Date:  2013-06-26       Impact factor: 2.714

5.  Neuromechanics of coordination during swallowing in Aplysia californica.

Authors:  Hui Ye; Douglas W Morton; Hillel J Chiel
Journal:  J Neurosci       Date:  2006-02-01       Impact factor: 6.167

6.  Mechanical reconfiguration mediates swallowing and rejection in Aplysia californica.

Authors:  Valerie A Novakovic; Gregory P Sutton; David M Neustadter; Randall D Beer; Hillel J Chiel
Journal:  J Comp Physiol A Neuroethol Sens Neural Behav Physiol       Date:  2006-04-04       Impact factor: 1.836

7.  Coherence analysis of muscle activity during quiet stance.

Authors:  Mark Saffer; Tim Kiemel; John Jeka
Journal:  Exp Brain Res       Date:  2007-10-23       Impact factor: 1.972

8.  Inter-joint coupling effects on muscle contributions to endpoint force and acceleration in a musculoskeletal model of the cat hindlimb.

Authors:  Keith W van Antwerp; Thomas J Burkholder; Lena H Ting
Journal:  J Biomech       Date:  2007-07-20       Impact factor: 2.712

9.  Changes in muscle activity and kinematics of highly trained cyclists during fatigue.

Authors:  Jonathan B Dingwell; Jason E Joubert; Fernando Diefenthaeler; Joel D Trinity
Journal:  IEEE Trans Biomed Eng       Date:  2008-11       Impact factor: 4.538

10.  A model of the lower limb for analysis of human movement.

Authors:  Edith M Arnold; Samuel R Ward; Richard L Lieber; Scott L Delp
Journal:  Ann Biomed Eng       Date:  2009-12-03       Impact factor: 3.934

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