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

Moissenet, F ORCID: https://orcid.org/0000-0001-6479-1911, Leboeuf, F ORCID: https://orcid.org/0000-0002-6483-9150 and Armand, S ORCID: https://orcid.org/0000-0001-9144-4982 2019, 'Lower limb sagittal gait kinematics can be predicted based on walking speed, gender, age and BMI.' , Scientific Reports, 9 (1) , p. 9510.

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Abstract

Clinical gait analysis attempts to provide, in a pathological context, an objective record that quantifies the magnitude of deviations from normal gait. However, the identification of deviations is highly dependent with the characteristics of the normative database used. In particular, a mismatch between patient characteristics and an asymptomatic population database in terms of walking speed, demographic and anthropometric parameters may lead to misinterpretation during the clinical process. Rather than developing a new normative data repository that may require considerable of resources and time, this study aims to assess a method for predicting lower limb sagittal kinematics using multiple regression models based on walking speed, gender, age and BMI as predictors. With this approach, we were able to predict kinematics with an error within 1 standard deviation of the mean of the original waveforms recorded on fifty-four participants. Furthermore, the proposed approach allowed us to estimate the relative contribution to angular variations of each predictor, independently from the others. It appeared that a mismatch in walking speed, but also age, sex and BMI may lead to errors higher than 5° on lower limb sagittal kinematics and should thus be taken into account before any clinical interpretation.

Item Type: Article
Additional Information: ** From Europe PMC via Jisc Publications Router ** Licence for this article: cc by **Journal IDs: essn 2045-2322; issn 2045-2322; nlmid 101563288 **Article IDs: pmcid: PMC6606631; pmid: 31267006 **History: published_online 02-07-2019; published 01-07-2019
Schools: Schools > School of Health and Society
Journal or Publication Title: Scientific Reports
Publisher: Nature Publishing Group
ISSN: 2045-2322
Related URLs:
Funders: Swiss National Science Foundation
SWORD Depositor: Publications Router
Depositing User: Publications Router
Date Deposited: 24 Oct 2019 14:50
Last Modified: 24 Oct 2019 15:00
URI: http://usir.salford.ac.uk/id/eprint/51939

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