Literature DB >> 27088395

Use of a backpack alters gait initiation of high school students.

Marcus Fraga Vieira1, Georgia Cristina Lehnen2, Matias Noll2, Fábio Barbosa Rodrigues2, Ivan Silveira de Avelar2, Paula Hentschel Lobo da Costa3.   

Abstract

We assessed how backpack carriage influences the gait initiation (GI) process in high school students, who extensively use backpacks. GI involves different dynamics from gait itself, while the excessive use of backpacks can result in adverse effects. 117 high school students were evaluated in three experimental conditions: no backpack (NB), bilateral backpack (BB), and unilateral backpack (UB). Two force plates were used to acquire ground reaction forces (GRFs) and moments for each foot separately. Center of pressure (COP) scalar variables were extracted, and statistical parametric mapping analysis was performed over the entire COP/GRFs time series. GI anticipatory postural adjustments (APAs) were reduced and were faster in backpack conditions; medial-lateral COP excursion was smaller in this phase. The uneven distribution of the extra load in the UB condition led to a larger medial-lateral COP shift in the support-foot unloading phase, with a corresponding vertical GRF change that suggests a more pronounced unloading swing foot/loading support foot mechanism. The anterior-posterior GRFs were altered, but the COP was not. A possible explanation for these results may be the forward trunk lean and the center of mass proximity of the base of support boundary, which induced smaller and faster APA, increased swing foot/support foot weight transfer, and increased load transfer to the first step.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Anticipatory postural adjustments; Backpack; Center of pressure; Gait initiation; Statistical parametric mapping

Mesh:

Year:  2016        PMID: 27088395     DOI: 10.1016/j.jelekin.2016.03.008

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


  1 in total

1.  The Impact of Load Style Variation on Gait Recognition Based on sEMG Images Using a Convolutional Neural Network.

Authors:  Xianfu Zhang; Yuping Hu; Ruimin Luo; Chao Li; Zhichuan Tang
Journal:  Sensors (Basel)       Date:  2021-12-15       Impact factor: 3.576

  1 in total

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