Literature DB >> 27131201

The gait standard deviation, a single measure of kinematic variability.

Morgan Sangeux1, Elyse Passmore2, H Kerr Graham3, Oren Tirosh4.   

Abstract

Measurement of gait kinematic variability provides relevant clinical information in certain conditions affecting the neuromotor control of movement. In this article, we present a measure of overall gait kinematic variability, GaitSD, based on combination of waveforms' standard deviation. The waveform standard deviation is the common numerator in established indices of variability such as Kadaba's coefficient of multiple correlation or Winter's waveform coefficient of variation. Gait data were collected on typically developing children aged 6-17 years. Large number of strides was captured for each child, average 45 (SD: 11) for kinematics and 19 (SD: 5) for kinetics. We used a bootstrap procedure to determine the precision of GaitSD as a function of the number of strides processed. We compared the within-subject, stride-to-stride, variability with the, between-subject, variability of the normative pattern. Finally, we investigated the correlation between age and gait kinematic, kinetic and spatio-temporal variability. In typically developing children, the relative precision of GaitSD was 10% as soon as 6 strides were captured. As a comparison, spatio-temporal parameters required 30 strides to reach the same relative precision. The ratio stride-to-stride divided by normative pattern variability was smaller in kinematic variables (the smallest for pelvic tilt, 28%) than in kinetic and spatio-temporal variables (the largest for normalised stride length, 95%). GaitSD had a strong, negative correlation with age. We show that gait consistency may stabilise only at, or after, skeletal maturity.
Copyright © 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Gait; Typically developing; Variability

Mesh:

Year:  2016        PMID: 27131201     DOI: 10.1016/j.gaitpost.2016.03.015

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


  4 in total

1.  A Decision Support System to Facilitate Identification of Musculoskeletal Impairments and Propose Recommendations Using Gait Analysis in Children With Cerebral Palsy.

Authors:  Kohleth Chia; Igor Fischer; Pam Thomason; H Kerr Graham; Morgan Sangeux
Journal:  Front Bioeng Biotechnol       Date:  2020-11-27

2.  Are Clinical Impairments Related to Kinematic Gait Variability in Children and Young Adults With Cerebral Palsy?

Authors:  Anne Tabard-Fougère; Dionys Rutz; Annie Pouliot-Laforte; Geraldo De Coulon; Christopher J Newman; Stéphane Armand; Jennifer Wegrzyk
Journal:  Front Hum Neurosci       Date:  2022-03-02       Impact factor: 3.169

Review 3.  Critical review of the use and scientific basis of forensic gait analysis.

Authors:  Nina M van Mastrigt; Kevin Celie; Arjan L Mieremet; Arnout C C Ruifrok; Zeno Geradts
Journal:  Forensic Sci Res       Date:  2018-10-09

4.  Overground Walking in a Fully Immersive Virtual Reality: A Comprehensive Study on the Effects on Full-Body Walking Biomechanics.

Authors:  Brian Horsak; Mark Simonlehner; Lucas Schöffer; Bernhard Dumphart; Arian Jalaeefar; Matthias Husinsky
Journal:  Front Bioeng Biotechnol       Date:  2021-12-03
  4 in total

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