Literature DB >> 29304432

The largest Lyapunov exponent of gait in young and elderly individuals: A systematic review.

Sina Mehdizadeh1.   

Abstract

The largest Lyapunov exponent (LyE) is an accepted method to quantify gait stability in young and old adults. However, a range of LyE values has been reported in the literature for healthy young and elderly adults in normal walking. Therefore, it has been impractical to use the LyE as a clinical measure of gait stability. The aims of this systematic review were to summarize different methodological approaches of quantifying LyE, as well as to classify LyE values of different body segments and joints in young and elderly individuals during normal walking. The Pubmed, Ovid Medline, Scopus and ISI Web of Knowledge databases were searched using keywords related to gait, stability, variability, and LyE. Only English language articles using the Lyapunov exponent to quantify the stability of healthy normal young and old subjects walking on a level surface were considered. 102 papers were included for full-text review and data extraction. Data associated with the walking surface, data recording method, sampling rate, walking speed, body segments and joints, number of strides/steps, variable type, filtering, time-normalizing, state space dimension, time delay, LyE algorithm, and the LyE values were extracted. The disparity in implementation and calculation of the LyE was from, (i) experiment design, (ii) data pre-processing, and (iii) LyE calculation method. For practical implementation of LyE as a measure of gait stability in clinical settings, a standard and universally accepted approach of calculating LyE is required. Therefore, future studies should look for a standard and generalized procedure to apply and calculate LyE.
Copyright © 2017 Elsevier B.V. All rights reserved.

Keywords:  Biomechanics; Dynamic stability; Motor control; Walking

Mesh:

Year:  2017        PMID: 29304432     DOI: 10.1016/j.gaitpost.2017.12.016

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


  14 in total

1.  Effect of data length on time delay and embedding dimension for calculating the Lyapunov exponent in walking.

Authors:  Victoria Smith Hussain; Mark L Spano; Thurmon E Lockhart
Journal:  J R Soc Interface       Date:  2020-07-15       Impact factor: 4.118

2.  Does local dynamic stability during unperturbed walking predict the response to balance perturbations? An examination across age and falls history.

Authors:  Mu Qiao; Kinh N Truong; Jason R Franz
Journal:  Gait Posture       Date:  2018-03-05       Impact factor: 2.840

Review 3.  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

4.  The Maximum Lyapunov Exponent During Walking and Running: Reliability Assessment of Different Marker-Sets.

Authors:  Antonis Ekizos; Alessandro Santuz; Arno Schroll; Adamantios Arampatzis
Journal:  Front Physiol       Date:  2018-08-24       Impact factor: 4.566

5.  A method to concatenate multiple short time series for evaluating dynamic behaviour during walking.

Authors:  Stefan Orter; Deepak K Ravi; Navrag B Singh; Florian Vogl; William R Taylor; Niklas König Ignasiak
Journal:  PLoS One       Date:  2019-06-21       Impact factor: 3.240

6.  Complexity of human walking: the attractor complexity index is sensitive to gait synchronization with visual and auditory cues.

Authors:  Philippe Terrier
Journal:  PeerJ       Date:  2019-08-01       Impact factor: 2.984

7.  Assessment of Local Dynamic Stability in Gait Based on Univariate and Multivariate Time Series.

Authors:  Henryk Josiński; Adam Świtoński; Agnieszka Michalczuk; Piotr Grabiec; Magdalena Pawlyta; Konrad Wojciechowski
Journal:  Comput Math Methods Med       Date:  2019-07-25       Impact factor: 2.238

8.  Stabilization demands of walking modulate the vestibular contributions to gait.

Authors:  Rina M Magnani; Sjoerd M Bruijn; Jaap H van Dieën; Patrick A Forbes
Journal:  Sci Rep       Date:  2021-07-02       Impact factor: 4.379

9.  Dynamic stability and spatiotemporal parameters during turning in healthy young adults.

Authors:  Chuan He; Rui Xu; Meidan Zhao; Yongming Guo; Shenglong Jiang; Feng He; Dong Ming
Journal:  Biomed Eng Online       Date:  2018-09-21       Impact factor: 2.819

10.  The detection of age groups by dynamic gait outcomes using machine learning approaches.

Authors:  Yuhan Zhou; Robbin Romijnders; Clint Hansen; Jos van Campen; Walter Maetzler; Tibor Hortobágyi; Claudine J C Lamoth
Journal:  Sci Rep       Date:  2020-03-10       Impact factor: 4.379

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.