Literature DB >> 19782569

Control of the upper body movements during level walking in patients with facioscapulohumeral dystrophy.

M Iosa1, C Mazzà, F Pecoraro, I Aprile, E Ricci, A Cappozzo.   

Abstract

Facioscapulohumeral dystrophy (FSHD) is a muscular disease usually spreading from upper to lower body and characterised by asymmetric muscle weakness. Walking ability is compromised in these patients, with a consequent high risk of falls. A quantitative analysis of the upper body oscillations may unveil useful information about the capacity of these patients to stabilise the head, maintain balance, and compensate for lower limb muscle weakness during walking. This study involved 13 patients with FSHD and 13 healthy volunteers. The trajectories of three points located on the cranio-caudal axis, at head, shoulder, and pelvis levels, during level walking, were analysed. The range of motion of these three points and the attenuation of the relevant accelerations going from pelvis to head level were used to describe the upper body movements during walking. The patients had wider and less symmetrical oscillations than the healthy controls both in antero-posterior and medio-lateral directions. Furthermore, the capacity of the patients to attenuate the accelerations going from pelvis to head level was reduced. These features may be related not only to upper body muscle weakness, but also to a strategy functional to the compensation of proximal leg muscle weakness. In conclusion, this study highlighted that the control of upper body oscillations and of head stability is reduced in patients with FSHD, suggesting that the assessment of the upper body movements should be included in the treatment decision process. Copyright 2009 Elsevier B.V. All rights reserved.

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Year:  2009        PMID: 19782569     DOI: 10.1016/j.gaitpost.2009.08.247

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


  9 in total

1.  Upper body kinematics in patients with cerebellar ataxia.

Authors:  Carmela Conte; Francesco Pierelli; Carlo Casali; Alberto Ranavolo; Francesco Draicchio; Giovanni Martino; Mahmoud Harfoush; Luca Padua; Gianluca Coppola; Giorgio Sandrini; Mariano Serrao
Journal:  Cerebellum       Date:  2014-12       Impact factor: 3.847

2.  Accelerometry reveals differences in gait variability between patients with multiple sclerosis and healthy controls.

Authors:  Jessie M Huisinga; Martina Mancini; Rebecca J St George; Fay B Horak
Journal:  Ann Biomed Eng       Date:  2012-11-18       Impact factor: 3.934

3.  Camptocormia phenotype of FSHD: a clinical and MRI study on six patients.

Authors:  Berit Jordan; Katharina Eger; Sabrina Koesling; Stephan Zierz
Journal:  J Neurol       Date:  2010-12-17       Impact factor: 4.849

4.  Sudden stopping in patients with cerebellar ataxia.

Authors:  Mariano Serrao; Carmela Conte; Carlo Casali; Alberto Ranavolo; Silvia Mari; Roberto Di Fabio; Armando Perrotta; Gianluca Coppola; Luca Padua; Stefano Monamì; Giorgio Sandrini; Francesco Pierelli
Journal:  Cerebellum       Date:  2013-10       Impact factor: 3.847

5.  Effects of walking endurance reduction on gait stability in patients with stroke.

Authors:  M Iosa; G Morone; A Fusco; L Pratesi; M Bragoni; P Coiro; M Multari; V Venturiero; D De Angelis; S Paolucci
Journal:  Stroke Res Treat       Date:  2011-09-28

6.  Effects of visual deprivation on gait dynamic stability.

Authors:  Marco Iosa; Augusto Fusco; Giovanni Morone; Stefano Paolucci
Journal:  ScientificWorldJournal       Date:  2012-05-03

Review 7.  Development and decline of upright gait stability.

Authors:  Marco Iosa; Augusto Fusco; Giovanni Morone; Stefano Paolucci
Journal:  Front Aging Neurosci       Date:  2014-02-05       Impact factor: 5.750

8.  Integration of human walking gyroscopic data using empirical mode decomposition.

Authors:  Vincent Bonnet; Sofiane Ramdani; Christine Azevedo-Coste; Philippe Fraisse; Claudia Mazzà; Aurelio Cappozzo
Journal:  Sensors (Basel)       Date:  2013-12-27       Impact factor: 3.576

9.  Artificial Neural Network Analyzing Wearable Device Gait Data for Identifying Patients With Stroke Unable to Return to Work.

Authors:  Marco Iosa; Edda Capodaglio; Silvia Pelà; Benedetta Persechino; Giovanni Morone; Gabriella Antonucci; Stefano Paolucci; Monica Panigazzi
Journal:  Front Neurol       Date:  2021-05-19       Impact factor: 4.003

  9 in total

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