Literature DB >> 18434159

Kinematic angular parameters in PD: reliability of joint angle curves and comparison with healthy subjects.

Arnaud Delval1, Julia Salleron, Jean-Louis Bourriez, Séverine Bleuse, Caroline Moreau, Pierre Krystkowiak, Luc Defebvre, Patrick Devos, Alain Duhamel.   

Abstract

BACKGROUND: Most previous biomechanical studies of Parkinson's disease (PD) have been restricted to the description of spatiotemporal parameters and certain peak values for angular parameters. The reliability of joint angle curves and comparisons with control data are of major interest in PD, since variability in gait cycle timing is a feature of this pathology.
METHODS: We used a video motion analysis system to record kinematic, spatiotemporal and angular parameters in 32 'off-drug' PD patients. The reliability of the patients' lower limb joint angle curves in the sagittal plane were analysed using the intra-class correlation coefficient (ICC), together with fast Fourier transform (FFT) analysis and hierarchical classification for discarding deviant curves. Lastly, we compared average curves (using a mixed model and the bootstrap method) for the less-affected and more-affected sides of PD patients and then compared the patient data with the results from 30 age-matched controls.
RESULTS: The ICC-based procedure was easily applicable. Only 9.4% and 12.5% of the patients' hip and knee curves (respectively) were deemed to be unreliable. However, the PD patients' very high cycle-to-cycle variability in the sagittal plane ankle curves prevented us from applying to this joint. For the knee joint, the curves for the most disabled patients (who walked at below 0.5 m/s) were not reliable. We did not find any differences between the less and more disabled sides. The differences between patient and control curves concerned the double-support time during the stance phase and the time point for maximum knee flexion during the swing phase. Patients and controls differed in terms of the hip extension phase, with lower values in PD.
CONCLUSION: We have developed the use of validated statistic tools for unambiguously comparing PD patients and controls in terms of joint angle curve differences.

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Year:  2008        PMID: 18434159     DOI: 10.1016/j.gaitpost.2008.03.003

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


  6 in total

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Authors:  Timothy A Thrasher; John S Ward; Stanley Fisher
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2.  Assessment of waveform similarity in clinical gait data: the linear fit method.

Authors:  M Iosa; A Cereatti; A Merlo; I Campanini; S Paolucci; A Cappozzo
Journal:  Biomed Res Int       Date:  2014-07-13       Impact factor: 3.411

3.  Gait profile score and movement analysis profile in patients with Parkinson's disease during concurrent cognitive load.

Authors:  Danielli S Speciali; Elaine M Oliveira; Jefferson R Cardoso; João C F Correa; Richard Baker; Paulo R G Lucareli
Journal:  Braz J Phys Ther       Date:  2014-07-18       Impact factor: 3.377

4.  Metronome Cueing of Walking Reduces Gait Variability after a Cerebellar Stroke.

Authors:  Rachel L Wright; Joseph W Bevins; David Pratt; Catherine M Sackley; Alan M Wing
Journal:  Front Neurol       Date:  2016-06-01       Impact factor: 4.003

5.  Mechanical Energy Recovery during Walking in Patients with Parkinson Disease.

Authors:  Mariangela Dipaola; Esteban E Pavan; Andrea Cattaneo; Giuseppe Frazzitta; Gianni Pezzoli; Paolo Cavallari; Carlo A Frigo; Ioannis U Isaias
Journal:  PLoS One       Date:  2016-06-03       Impact factor: 3.240

6.  Effect of Trunk Muscle Strengthening on Gait Pattern and Falls in Parkinson's Disease.

Authors:  Emma Bestaven; Etienne Guillaud; Mathieu De Sèze; Aupy Jerome; Pierre Burbaud; Jean-René Cazalets; Dominique Guehl
Journal:  J Rehabil Med Clin Commun       Date:  2019-01-28
  6 in total

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