Literature DB >> 20719661

EMG patterns during running: Intra- and inter-individual variability.

L Guidetti1, G Rivellini, F Figura.   

Abstract

Rectified surface electromyographic (EMG) patterns of five healthy, young, physically-fit subjects running at 4.2 m s(-1) on a treadmill were recorded with the objective of defining a normal profile of EMG activity for running gait. This knowledge is important in understanding how the central nervous system (CNS) controls simple running tasks under normal conditions. The EMG signals from seven muscles (erector spinae, rectus femoris, vastus medialis, vastus lateralis, biceps femoris, tibialis anterior and gastrocnemius) were recorded, together with footswitch signals. The intra- and inter-individual variability of each muscle's EMG profile and peak times were analysed. Interindividual EMG peak time values were analysed to define the timing of the activity of the muscles studied relative to the stride cycle and its subphases. For each muscle, little variation was found within individuals in EMG profile and peak time across trials, but differences between subjects were significant (P < 0.01). EMG peak time analysis showed two distinct activation sequences of different muscles: the first at stance phase and the second at terminal swing. In conclusion, in spite of a significant variability among subjects in EMG profile and peak time values for each muscle, the EMG peak timing analysis showed a sequence of activation at stance phase, no EMG peak activity during the first double swing and another sequence of activation during terminal swing. These findings are evidence of a neuromuscular control strategy common to all subjects.

Year:  1996        PMID: 20719661     DOI: 10.1016/1050-6411(95)00015-1

Source DB:  PubMed          Journal:  J Electromyogr Kinesiol        ISSN: 1050-6411            Impact factor:   2.368


  18 in total

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Journal:  Front Comput Neurosci       Date:  2012-12-28       Impact factor: 2.380

7.  A method for a categorized and probabilistic analysis of the surface electromyogram in dynamic contractions.

Authors:  Sylvie C F A Von Werder; Tim Kleiber; Catherine Disselhorst-Klug
Journal:  Front Physiol       Date:  2015-02-11       Impact factor: 4.566

8.  Space-by-Time Modular Decomposition Effectively Describes Whole-Body Muscle Activity During Upright Reaching in Various Directions.

Authors:  Pauline M Hilt; Ioannis Delis; Thierry Pozzo; Bastien Berret
Journal:  Front Comput Neurosci       Date:  2018-04-03       Impact factor: 2.380

9.  Subspace identification and classification of healthy human gait.

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Journal:  PLoS One       Date:  2013-07-08       Impact factor: 3.240

10.  Intra-Individual Variability of Surface Electromyography in Front Crawl Swimming.

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Journal:  PLoS One       Date:  2015-12-16       Impact factor: 3.240

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