Literature DB >> 28433389

Comparison of methodologies to assess muscle co-contraction during gait.

H Souissi1, R Zory2, J Bredin3, P Gerus2.   

Abstract

The aim of this study was to compare co-contraction index (CCI) computed from muscle moments to different co-activation indexes (Co-Act) derived from EMG data at the ankle and the knee joint during gait. An EMG-driven model was used to estimate muscle moments during over-ground walking gait at a self-selected velocity from twelve healthy subjects. The CCI calculated from muscle moments was compared with three Co-Acts estimated from the normalized EMG data. The co-activation methods produced lower values than the CCI during the first double-support and the swing phase at the ankle joint and during the stance phase at the knee joint. The co-activation methods trend is to underestimate the simultaneous action of agonist and antagonist contraction. Because the EMG-driven model included the muscle mechanical properties (e.g. force-length-velocity relationship) and muscle moment-arm, the co-contraction based on major agonist and antagonist muscle moment may provide a more confident description of muscle action compared to co-activation indexes.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Keywords:  Co-contraction; EMG activity; EMG-driven modeling; Gait; Muscle moment

Mesh:

Year:  2017        PMID: 28433389     DOI: 10.1016/j.jbiomech.2017.03.029

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


  8 in total

1.  High muscle co-contraction does not result in high joint forces during gait in anterior cruciate ligament deficient knees.

Authors:  Ashutosh Khandha; Kurt Manal; Jacob Capin; Elizabeth Wellsandt; Adam Marmon; Lynn Snyder-Mackler; Thomas S Buchanan
Journal:  J Orthop Res       Date:  2018-10-09       Impact factor: 3.494

Review 2.  Muscle coactivation: definitions, mechanisms, and functions.

Authors:  Mark L Latash
Journal:  J Neurophysiol       Date:  2018-03-28       Impact factor: 2.714

3.  Muscle Co-Contraction Detection in the Time-Frequency Domain.

Authors:  Francesco Di Nardo; Martina Morano; Annachiara Strazza; Sandro Fioretti
Journal:  Sensors (Basel)       Date:  2022-06-28       Impact factor: 3.847

4.  The neuromuscular responses in patients with Parkinson's disease under different conditions during whole-body vibration training.

Authors:  Chia-Ming Chang; Chon-Haw Tsai; Ming-Kuei Lu; Hsin-Chun Tseng; Grace Lu; Bey-Ling Liu; Hsiu-Chen Lin
Journal:  BMC Complement Med Ther       Date:  2022-01-03

5.  Auditory sEMG biofeedback for reducing muscle co-contraction during pedaling.

Authors:  Benio Kibushi; Junichi Okada
Journal:  Physiol Rep       Date:  2022-05

6.  Isokinetic angle-specific moments and ratios characterizing hamstring and quadriceps strength in anterior cruciate ligament deficient knees.

Authors:  Hongshi Huang; Jianqiao Guo; Jie Yang; Yanfang Jiang; Yuanyuan Yu; Steffen Müller; Gexue Ren; Yingfang Ao
Journal:  Sci Rep       Date:  2017-08-04       Impact factor: 4.379

7.  How Well Do Commonly Used Co-contraction Indices Approximate Lower Limb Joint Stiffness Trends During Gait for Individuals Post-stroke?

Authors:  Geng Li; Mohammad S Shourijeh; Di Ao; Carolynn Patten; Benjamin J Fregly
Journal:  Front Bioeng Biotechnol       Date:  2021-01-07

8.  Increased ankle muscle coactivation in the early stages of multiple sclerosis.

Authors:  L Eduardo Cofré Lizama; Andisheh Bastani; Anneke van der Walt; Trevor Kilpatrick; Fary Khan; Mary P Galea
Journal:  Mult Scler J Exp Transl Clin       Date:  2020-02-11
  8 in total

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