Literature DB >> 30523377

Do individual differences in the distribution of activation between synergist muscles reflect individual strategies?

Marion Crouzier1, François Hug1,2,3, Sylvain Dorel1, Thibault Deschamps1, Kylie Tucker2,4, Lilian Lacourpaille5.   

Abstract

Individual differences in the distribution of activation between synergist muscles have been reported during a wide variety of tasks. Whether these differences represent actual individual strategies is unknown. The aims of this study were to: (i) test the between-day reliability of the distribution of activation between synergist muscles, (ii) to determine the robustness of these strategies between tasks, and to (iii) describe the inter-individual variability of activation strategies in a large sample size. Eighty-five volunteers performed a series of single-joint isometric tasks with their dominant leg [knee extension and plantarflexion at 25% of maximal voluntary contraction (MVC)] and locomotor tasks (pedalling and walking). Of these participants, 62 performed a second experimental session that included the isometric tasks. Myoelectrical activity of six lower limb muscles (the three superficial heads of the quadriceps and the three heads of the triceps surae) was measured using surface electromyography (EMG) and normalized to that measured during MVC. When considering isometric contractions, distribution of normalized EMG amplitude among synergist muscles, considered here as activation strategies, was highly variable between individuals (15.8% < CV < 42.7%) and robust across days (0.57 < ICC < 0.82). In addition, individual strategies observed during simple single-joint tasks were correlated with those observed during locomotor tasks [0.37 < r < 0.76 for quadriceps (n = 83); 0.30 < r < 0.66 for triceps surae (n = 82); all P < 0.001]. Our results provide evidence that people who bias their activation to a particular muscle do so during multiple tasks. Even though inter-individual variability of EMG signals has been well described, it is often considered noise which complicates the interpretation of data. This study provides evidence that variability results from actual differences in activation strategies.

Entities:  

Keywords:  Electromyography; Gait; Muscle coordination; Pedalling

Mesh:

Year:  2018        PMID: 30523377     DOI: 10.1007/s00221-018-5445-6

Source DB:  PubMed          Journal:  Exp Brain Res        ISSN: 0014-4819            Impact factor:   1.972


  39 in total

1.  Activation linearity and parallelism of the superficial quadriceps across the isometric intensity spectrum.

Authors:  D M Pincivero; A J Coelho
Journal:  Muscle Nerve       Date:  2000-03       Impact factor: 3.217

2.  Measures of reliability in sports medicine and science.

Authors:  W G Hopkins
Journal:  Sports Med       Date:  2000-07       Impact factor: 11.136

Review 3.  Optimization-based models of muscle coordination.

Authors:  Boris I Prilutsky; Vladimir M Zatsiorsky
Journal:  Exerc Sport Sci Rev       Date:  2002-01       Impact factor: 6.230

4.  Control of foot trajectory in human locomotion: role of ground contact forces in simulated reduced gravity.

Authors:  Y P Ivanenko; R Grasso; V Macellari; F Lacquaniti
Journal:  J Neurophysiol       Date:  2002-06       Impact factor: 2.714

5.  Development of recommendations for SEMG sensors and sensor placement procedures.

Authors:  H J Hermens; B Freriks; C Disselhorst-Klug; G Rau
Journal:  J Electromyogr Kinesiol       Date:  2000-10       Impact factor: 2.368

6.  International physical activity questionnaire: 12-country reliability and validity.

Authors:  Cora L Craig; Alison L Marshall; Michael Sjöström; Adrian E Bauman; Michael L Booth; Barbara E Ainsworth; Michael Pratt; Ulf Ekelund; Agneta Yngve; James F Sallis; Pekka Oja
Journal:  Med Sci Sports Exerc       Date:  2003-08       Impact factor: 5.411

Review 7.  Optimality principles in sensorimotor control.

Authors:  Emanuel Todorov
Journal:  Nat Neurosci       Date:  2004-09       Impact factor: 24.884

8.  Influence of amplitude cancellation on the simulated surface electromyogram.

Authors:  Kevin G Keenan; Dario Farina; Katrina S Maluf; Roberto Merletti; Roger M Enoka
Journal:  J Appl Physiol (1985)       Date:  2004-09-17

Review 9.  The extraction of neural strategies from the surface EMG.

Authors:  Dario Farina; Roberto Merletti; Roger M Enoka
Journal:  J Appl Physiol (1985)       Date:  2004-04

10.  Random change in cortical load representation suggests distinct control of posture and movement.

Authors:  Isaac Kurtzer; Troy M Herter; Stephen H Scott
Journal:  Nat Neurosci       Date:  2005-03-13       Impact factor: 24.884

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