Literature DB >> 19073812

Neuromechanics of muscle synergies during cycling.

James M Wakeling1, Tamara Horn.   

Abstract

Muscle synergies have been proposed as building blocks that could simplify the construction of motor behaviors. However, the muscles within synergistic groups may have different architectures, mechanical linkages to the skeleton, and biochemical properties, and these put competing demands on the most appropriate way to activate them for different mechanical tasks. This study identifies the extent to which synergistic patterns of muscle activity vary when the mechanical demands on a limb were altered, and additionally identifies how consistent the spectral profiles of the electromyographic (EMG) intensities were across the different movement tasks. The muscle activities were measured with surface EMG across 10 muscles in the leg during cycling at a range of loads and velocities. The EMGs were quantified by their intensities in time-frequency space using wavelet analysis; the instantaneous patterns of activity identified using principal component analysis, statistically compared and further visualized using the varimax rotation. Variability (35.7%) in the patterns of activity between the muscles were correlated with the torque and velocity of the pedal crank. Anatomic groups of muscles share a common mechanical action across a joint; uncoupling between such muscles was identified in 68.8% of the varimax patterns that encompassed all 10 muscles and 20.8-29.5% of the activity patterns when the anatomic groups were analyzed separately. The EMG spectra showed greatest heterogeneity for the gastrocnemii. These results show that the activity of muscles within anatomic groups is partially uncoupled in response to altered mechanical demands on the limb.

Mesh:

Year:  2008        PMID: 19073812     DOI: 10.1152/jn.90679.2008

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


  32 in total

Review 1.  Patterned control of human locomotion.

Authors:  Francesco Lacquaniti; Yuri P Ivanenko; Myrka Zago
Journal:  J Physiol       Date:  2012-03-12       Impact factor: 5.182

2.  Extracting synergies in gait: using EMG variability to evaluate control strategies.

Authors:  Rajiv Ranganathan; Chandramouli Krishnan
Journal:  J Neurophysiol       Date:  2012-06-20       Impact factor: 2.714

3.  Muscle gearing during isotonic and isokinetic movements in the ankle plantarflexors.

Authors:  Avleen Randhawa; Meghan E Jackman; James M Wakeling
Journal:  Eur J Appl Physiol       Date:  2012-07-10       Impact factor: 3.078

4.  Muscle coordination limits efficiency and power output of human limb movement under a wide range of mechanical demands.

Authors:  Ollie M Blake; James M Wakeling
Journal:  J Neurophysiol       Date:  2015-10-07       Impact factor: 2.714

5.  Learning new gait patterns: Exploratory muscle activity during motor learning is not predicted by motor modules.

Authors:  Rajiv Ranganathan; Chandramouli Krishnan; Yasin Y Dhaher; William Z Rymer
Journal:  J Biomech       Date:  2016-02-10       Impact factor: 2.712

Review 6.  Movement mechanics as a determinate of muscle structure, recruitment and coordination.

Authors:  James M Wakeling; Ollie M Blake; Iris Wong; Manku Rana; Sabrina S M Lee
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2011-05-27       Impact factor: 6.237

7.  Effect of power output on muscle coordination during rowing.

Authors:  Nicolas A Turpin; Arnaud Guével; Sylvain Durand; François Hug
Journal:  Eur J Appl Physiol       Date:  2011-03-31       Impact factor: 3.078

8.  Is my model good enough? Best practices for verification and validation of musculoskeletal models and simulations of movement.

Authors:  Jennifer L Hicks; Thomas K Uchida; Ajay Seth; Apoorva Rajagopal; Scott L Delp
Journal:  J Biomech Eng       Date:  2015-01-26       Impact factor: 2.097

9.  Muscle Synergies of Untrained Subjects during 6 min Maximal Rowing on Slides and Fixed Ergometer.

Authors:  Shazlin Shaharudin; Damiano Zanotto; Sunil Agrawal
Journal:  J Sports Sci Med       Date:  2014-12-01       Impact factor: 2.988

10.  Why are Antagonist Muscles Co-activated in My Simulation? A Musculoskeletal Model for Analysing Human Locomotor Tasks.

Authors:  Adrian K M Lai; Allison S Arnold; James M Wakeling
Journal:  Ann Biomed Eng       Date:  2017-09-12       Impact factor: 3.934

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