Literature DB >> 21519716

Application of principal component analysis on gait kinematics in elderly women with knee osteoarthritis.

Renata N Kirkwood1, Renan A Resende, Cláudio M B Magalhães, Henrique A Gomes, Sueli A Mingoti, Rosana F Sampaio.   

Abstract

BACKGROUND: The applicability of gait analysis has been implemented with the introduction of the principal component analysis (PCA), a statistical data reduction technique that allows the comparison of the whole cycle between groups of individuals.
OBJECTIVES: Applying PCA, to compare the kinematics of the knee joint during gait, in the frontal and sagittal planes, between a group of elderly women with and without diagnosis in the initial and moderate stages of Osteoarthritis (OA).
METHODS: A total of 38 elderly women (69.6±8.1 years) with knee OA and 40 asymptomatic (70.3±7.7 years) participated on this study. The kinematics was obtained using the Qualisys Pro-reflex system.
RESULTS: The OA group showed decreased gait velocity and stride length (p<0.05) and was characterized with higher WOMAC pain score. In the frontal plane, the between-group differences of the components were not significant. In the sagittal plane, three principal components explained 99.7% of the data variance. Discriminant analysis indicated that component 2 and 3 could classify correctly 71.8% of the individuals. However, CP3, which captures the difference in the flexion knee angle magnitude during gait, was the variable with higher discrimination power between groups.
CONCLUSIONS: PCA is an effective multivariate statistical technique to analyse the kinematic gait waveform during the gait cycle. The smaller knee flexion angle in the OA group was appointed as a discriminatory factor between groups, therefore, it should be considered in the physical therapy evaluation and treatment of elderly women with knee OA.

Entities:  

Mesh:

Year:  2011        PMID: 21519716

Source DB:  PubMed          Journal:  Rev Bras Fisioter


  8 in total

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4.  Variations in kinematics during clinical gait analysis in stroke patients.

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5.  Spatiotemporal gait parameters and recurrent falls in community-dwelling elderly women: a prospective study.

Authors:  Bruno S Moreira; Rosana F Sampaio; Renata N Kirkwood
Journal:  Braz J Phys Ther       Date:  2014-11-28       Impact factor: 3.377

6.  Spatiotemporal and variability gait data in community-dwelling elderly women from Brazil.

Authors:  Renata N Kirkwood; Henrique A Gomes; Rosana F Sampaio; Sheyla R C Furtado; Bruno S Moreira
Journal:  Braz J Phys Ther       Date:  2016-03-22       Impact factor: 3.377

7.  Biomechanical Markers of Forward Hop-Landing After ACL-Reconstruction: A Pattern Recognition Approach.

Authors:  Prasanna Sritharan; Mario A Muñoz; Peter Pivonka; Adam L Bryant; Hossein Mokhtarzadeh; Luke G Perraton
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8.  Changes in movement organization and control strategies when learning a biomechanically constrained gait pattern, racewalking: a PCA study.

Authors:  L Majed; A M Heugas; I A Siegler
Journal:  Exp Brain Res       Date:  2016-12-10       Impact factor: 1.972

  8 in total

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