Literature DB >> 26282046

Gait variability and motor control in people with knee osteoarthritis.

Tine Alkjaer1, Peter C Raffalt2, Helle Dalsgaard2, Erik B Simonsen2, Nicolas C Petersen3, Henning Bliddal4, Marius Henriksen4.   

Abstract

Knee osteoarthritis (OA) is a common disease that impairs walking ability and function. We compared the temporal gait variability and motor control in people with knee OA with healthy controls. The purpose was to test the hypothesis that the temporal gait variability would reflect a more stereotypic pattern in people with knee OA compared with healthy age-matched subjects. To assess the gait variability the temporal structure of the ankle and knee joint kinematics was quantified by the largest Lyapunov exponent and the stride time fluctuations were quantified by sample entropy and detrended fluctuation analysis. The motor control was assessed by the soleus (SO) Hoffmann (H)-reflex modulation and muscle co-activation during walking. The results showed no statistically significant mean group differences in any of the gait variability measures or muscle co-activation levels. The SO H-reflex amplitude was significantly higher in the knee OA group around heel strike when compared with the controls. The mean group difference in the H-reflex in the initial part of the stance phase (control-knee OA) was -6.6% Mmax (95% CI: -10.4 to -2.7, p=0.041). The present OA group reported relatively small impact of their disease. These results suggest that the OA group in general sustained a normal gait pattern with natural variability but with suggestions of facilitated SO H-reflex in the swing to stance phase transition. We speculate that the difference in SO H-reflex modulation reflects that the OA group increased the excitability of the soleus stretch reflex as a preparatory mechanism to avoid sudden collapse of the knee joint which is not uncommon in knee OA.
Copyright © 2015 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Gait variability; H-reflex; Knee OA; Motor control; Walking

Mesh:

Year:  2015        PMID: 26282046     DOI: 10.1016/j.gaitpost.2015.07.063

Source DB:  PubMed          Journal:  Gait Posture        ISSN: 0966-6362            Impact factor:   2.840


  9 in total

1.  Sampling frequency influences sample entropy of kinematics during walking.

Authors:  Peter C Raffalt; John McCamley; William Denton; Jennifer M Yentes
Journal:  Med Biol Eng Comput       Date:  2018-11-03       Impact factor: 2.602

2.  On the application of entropic half-life and statistical persistence decay for quantification of time dependency in human gait.

Authors:  Peter C Raffalt; Jennifer M Yentes
Journal:  J Biomech       Date:  2020-06-13       Impact factor: 2.712

3.  Introducing Statistical Persistence Decay: A Quantification of Stride-to-Stride Time Interval Dependency in Human Gait.

Authors:  P C Raffalt; J M Yentes
Journal:  Ann Biomed Eng       Date:  2017-09-25       Impact factor: 3.934

Review 4.  Gait analysis under the lens of statistical physics.

Authors:  Massimiliano Zanin; Felipe Olivares; Irene Pulido-Valdeolivas; Estrella Rausell; David Gomez-Andres
Journal:  Comput Struct Biotechnol J       Date:  2022-06-18       Impact factor: 6.155

5.  Selection Procedures for the Largest Lyapunov Exponent in Gait Biomechanics.

Authors:  Peter C Raffalt; Jenny A Kent; Shane R Wurdeman; Nicholas Stergiou
Journal:  Ann Biomed Eng       Date:  2019-01-30       Impact factor: 3.934

6.  On the choice of multiscale entropy algorithm for quantification of complexity in gait data.

Authors:  Peter C Raffalt; William Denton; Jennifer M Yentes
Journal:  Comput Biol Med       Date:  2018-10-10       Impact factor: 4.589

7.  Accelerometer-Based Step Regularity Is Lower in Older Adults with Bilateral Knee Osteoarthritis.

Authors:  John M Barden; Christian A Clermont; Dylan Kobsar; Olivier Beauchet
Journal:  Front Hum Neurosci       Date:  2016-12-08       Impact factor: 3.169

8.  Modeling and classification of gait patterns between anterior cruciate ligament deficient and intact knees based on phase space reconstruction, Euclidean distance and neural networks.

Authors:  Wenbao Wu; Wei Zeng; Limin Ma; Chengzhi Yuan; Yu Zhang
Journal:  Biomed Eng Online       Date:  2018-11-01       Impact factor: 2.819

9.  Neuromuscular Function of the Knee Joint Following Knee Injuries: Does It Ever Get Back to Normal? A Systematic Review with Meta-Analyses.

Authors:  Beyza Tayfur; Chedsada Charuphongsa; Dylan Morrissey; Stuart Charles Miller
Journal:  Sports Med       Date:  2021-02       Impact factor: 11.136

  9 in total

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