Literature DB >> 28395170

The effects of walking speed on upper body kinematics during gait in healthy subjects.

Jacqueline Romkes1, Katrin Bracht-Schweizer2.   

Abstract

Patients undergoing a clinical gait analysis often walk slower than healthy people. However, data on how speed affects upper body movements, especially of the arms and shoulders, are scarce. Therefore, in this descriptive study, we examined how changes in walking speed affect upper-body kinematics and aspects of intersegmental coordination between upper and lower body during overground walking in a group of healthy adult subjects. Three-dimensional gait data were collected on 20 healthy subjects (aged between 22 and 31 years) walking at six speeds ranging from extremely slow to very fast. Our results showed significant speed-related changes of upper body kinematic movement curves in three aspects, namely in amplitude (curves for shoulder flexion and abduction, elbow flexion, pelvic obliquity and rotation), timing (curves for shoulder extension and abduction, elbow extension, pelvic rotation) and curve pattern (curves for shoulder and elbow flexion, shoulder rotation, pelvic tilt). The intersegmental coordination between the thorax and pelvis and arm and leg was also affected by a change of walking speed. Our data supplement the already available data in the literature examining the effects of walking speed on lower extremity motion. Furthermore, the data can be used as a reference for both basic biomechanical and clinical gait studies. The results will help in clinical practice to differentiate between effects caused by walking speed and underlying pathology.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Gait analysis; Healthy adults; Intersegmental coordination; Upper body kinematics; Walking speed

Mesh:

Year:  2017        PMID: 28395170     DOI: 10.1016/j.gaitpost.2017.03.025

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


  7 in total

1.  Lower limb sagittal gait kinematics can be predicted based on walking speed, gender, age and BMI.

Authors:  Florent Moissenet; Fabien Leboeuf; Stéphane Armand
Journal:  Sci Rep       Date:  2019-07-02       Impact factor: 4.379

2.  An artificial neural network approach to detect presence and severity of Parkinson's disease via gait parameters.

Authors:  Tiwana Varrecchia; Stefano Filippo Castiglia; Alberto Ranavolo; Carmela Conte; Antonella Tatarelli; Gianluca Coppola; Cherubino Di Lorenzo; Francesco Draicchio; Francesco Pierelli; Mariano Serrao
Journal:  PLoS One       Date:  2021-02-19       Impact factor: 3.240

3.  Using a Deep Learning Method and Data from Two-Dimensional (2D) Marker-Less Video-Based Images for Walking Speed Classification.

Authors:  Tasriva Sikandar; Mohammad F Rabbi; Kamarul H Ghazali; Omar Altwijri; Mahdi Alqahtani; Mohammed Almijalli; Saleh Altayyar; Nizam U Ahamed
Journal:  Sensors (Basel)       Date:  2021-04-17       Impact factor: 3.576

4.  A survey of human shoulder functional kinematic representations.

Authors:  Rakesh Krishnan; Niclas Björsell; Elena M Gutierrez-Farewik; Christian Smith
Journal:  Med Biol Eng Comput       Date:  2018-10-26       Impact factor: 2.602

5.  Gait kinematics of the hip, pelvis, and trunk associated with external hip adduction moment in patients with secondary hip osteoarthritis: toward determination of the key point in gait modification.

Authors:  Hiroshige Tateuchi; Haruhiko Akiyama; Koji Goto; Kazutaka So; Yutaka Kuroda; Noriaki Ichihashi
Journal:  BMC Musculoskelet Disord       Date:  2020-01-06       Impact factor: 2.362

6.  The nature and extent of upper limb associated reactions during walking in people with acquired brain injury.

Authors:  Michelle B Kahn; Ross A Clark; Gavin Williams; Kelly J Bower; Megan Banky; John Olver; Benjamin F Mentiplay
Journal:  J Neuroeng Rehabil       Date:  2019-12-27       Impact factor: 4.262

7.  Uniqueness of gait kinematics in a cohort study.

Authors:  Gunwoo Park; Kyoung Min Lee; Seungbum Koo
Journal:  Sci Rep       Date:  2021-07-27       Impact factor: 4.379

  7 in total

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