Literature DB >> 33490046

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

Geng Li1, Mohammad S Shourijeh1, Di Ao1, Carolynn Patten2, Benjamin J Fregly1.   

Abstract

Muscle co-contraction generates joint stiffness to improve stability and accuracy during limb movement but at the expense of higher energetic cost. However, quantification of joint stiffness is difficult using either experimental or computational means. In contrast, quantification of muscle co-contraction using an EMG-based Co-Contraction Index (CCI) is easier and may offer an alternative for estimating joint stiffness. This study investigated the feasibility of using two common CCIs to approximate lower limb joint stiffness trends during gait. Calibrated EMG-driven lower extremity musculoskeletal models constructed for two individuals post-stroke were used to generate the quantities required for CCI calculations and model-based estimation of joint stiffness. CCIs were calculated for various combinations of antagonist muscle pairs based on two common CCI formulations: Rudolph et al. (2000) (CCI 1) and Falconer and Winter (1985) (CCI 2). CCI 1 measures antagonist muscle activation relative to not only total activation of agonist plus antagonist muscles but also agonist muscle activation, while CCI 2 measures antagonist muscle activation relative to only total muscle activation. We computed the correlation between these two CCIs and model-based estimates of sagittal plane joint stiffness for the hip, knee, and ankle of both legs. Although we observed moderate to strong correlations between some CCI formulations and corresponding joint stiffness, these associations were highly dependent on the methodological choices made for CCI computation. Specifically, we found that: (1) CCI 1 was generally more correlated with joint stiffness than was CCI 2, (2) CCI calculation using EMG signals with calibrated electromechanical delay generally yielded the best correlations with joint stiffness, and (3) choice of antagonist muscle pairs significantly influenced CCI correlation with joint stiffness. By providing guidance on how methodological choices influence CCI correlation with joint stiffness trends, this study may facilitate a simpler alternate approach for studying joint stiffness during human movement.
Copyright © 2021 Li, Shourijeh, Ao, Patten and Fregly.

Entities:  

Keywords:  EMG-driven modeling; co-contraction index; electromyography (EMG); joint stiffness; muscle co-contraction

Year:  2021        PMID: 33490046      PMCID: PMC7817819          DOI: 10.3389/fbioe.2020.588908

Source DB:  PubMed          Journal:  Front Bioeng Biotechnol        ISSN: 2296-4185


  46 in total

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Authors:  Harald Böhm; Matthias Hösl
Journal:  J Biomech       Date:  2010-06-11       Impact factor: 2.712

2.  The role of cocontraction in the impairment of movement accuracy with fatigue.

Authors:  Olivier Missenard; Denis Mottet; Stephane Perrey
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Journal:  J Sci Med Sport       Date:  2013-10-18       Impact factor: 4.319

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7.  Effects of repeated ankle stretching on calf muscle-tendon and ankle biomechanical properties in stroke survivors.

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Journal:  Clin Biomech (Bristol, Avon)       Date:  2011-01-06       Impact factor: 2.063

8.  Development of a powered variable-stiffness exoskeleton device for elbow rehabilitation.

Authors:  Yi Liu; Shuxiang Guo; Hideyuki Hirata; Hidenori Ishihara; Takashi Tamiya
Journal:  Biomed Microdevices       Date:  2018-08-03       Impact factor: 2.838

9.  The effect of prolonged static and cyclic stretching on ankle joint stiffness, torque relaxation, and gait in people with stroke.

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Journal:  Phys Ther       Date:  2002-09

10.  Muscle Synergies Modify Optimization Estimates of Joint Stiffness During Walking.

Authors:  Mohammad S Shourijeh; Benjamin J Fregly
Journal:  J Biomech Eng       Date:  2020-01-01       Impact factor: 2.097

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  4 in total

1.  Upper Limbs Muscle Co-contraction Changes Correlated With the Impairment of the Corticospinal Tract in Stroke Survivors: Preliminary Evidence From Electromyography and Motor-Evoked Potential.

Authors:  Wenfei Sheng; Shijue Li; Jiangli Zhao; Yujia Wang; Zichong Luo; Wai Leung Ambrose Lo; Minghui Ding; Chuhuai Wang; Le Li
Journal:  Front Neurosci       Date:  2022-06-01       Impact factor: 5.152

2.  Increased co-contraction reaction during a surface perturbation is associated with unsuccessful postural control among older adults.

Authors:  Jimmy Falk; Viktor Strandkvist; Mascha Pauelsen; Irene Vikman; Lars Nyberg; Ulrik Röijezon
Journal:  BMC Geriatr       Date:  2022-05-19       Impact factor: 4.070

3.  Establishing the Role of Elbow Muscles by Evaluating Muscle Activation and Co-contraction Levels at Maximal External Rotation in Fastball Pitching.

Authors:  Bart van Trigt; Eva Galjee; Marco J M Hoozemans; Frans C T van der Helm; DirkJan H E J Veeger
Journal:  Front Sports Act Living       Date:  2021-11-30

4.  EMG-driven musculoskeletal model calibration with estimation of unmeasured muscle excitations via synergy extrapolation.

Authors:  Di Ao; Marleny M Vega; Mohammad S Shourijeh; Carolynn Patten; Benjamin J Fregly
Journal:  Front Bioeng Biotechnol       Date:  2022-09-07
  4 in total

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