Literature DB >> 12934087

Case for gait analysis as part of the management of incomplete spinal cord injury.

J H Patrick1.   

Abstract

Incomplete spinal cord injury at ASIA (D) level often leads to major gait re-education attempts for patients and staff. Walking prognosis usually depends upon muscle power loss, degree of spasticity present, type of lower limb joint deformity developing and availability of treatment. As an adjunct to physical examination and observation, instrumented gait analysis can inform treatment, since three-dimensional dynamic joint range motion (kinematics) and estimation of joint forces occurring at the hip, knee and especially ankle/foot (kinetics) can be combined with walking EMG and energy cost tests to understand fully a gait deficit. This should then assist the clinical decision-making process. Knowledge of the effects of any dynamic contracture on the available redundancy within ipsilateral limb joints, and information about muscle actions obtained by calculating joint forces (including moments and powers) improves overall knowledge of gait cycle abnormality. Such gait analysis has revolutionised the management of spasticity in walking cerebral palsy children by guiding surgical and other treatments. Similar improvements could be looked for in incomplete SCI patients whose gait pattern is not ideal. Dynamic energy cost estimations could also be used as an outcome measure to study improvements after treatment: whether this is orthotic, pharmacological or following physiotherapy or surgical techniques.

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Mesh:

Year:  2003        PMID: 12934087     DOI: 10.1038/sj.sc.3101524

Source DB:  PubMed          Journal:  Spinal Cord        ISSN: 1362-4393            Impact factor:   2.772


  8 in total

1.  Gait impairment in cervical spondylotic myelopathy: comparison with age- and gender-matched healthy controls.

Authors:  Ailish Malone; Dara Meldrum; Ciaran Bolger
Journal:  Eur Spine J       Date:  2012-07-24       Impact factor: 3.134

2.  Gait kinematic analysis in patients with a mild form of central cord syndrome.

Authors:  Angel Gil-Agudo; Soraya Pérez-Nombela; Arturo Forner-Cordero; Enrique Pérez-Rizo; Beatriz Crespo-Ruiz; Antonio del Ama-Espinosa
Journal:  J Neuroeng Rehabil       Date:  2011-02-02       Impact factor: 4.262

3.  Predicting knee osteoarthritis risk in injured populations.

Authors:  Michael J Long; Enrica Papi; Lynsey D Duffell; Alison H McGregor
Journal:  Clin Biomech (Bristol, Avon)       Date:  2017-06-12       Impact factor: 2.063

4.  Reliability of three-dimensional kinematic gait data in adults with spinal cord injury.

Authors:  Pia Wedege; Kathrin Steffen; Vegard Strøm; Arve Isak Opheim
Journal:  J Rehabil Assist Technol Eng       Date:  2017-09-14

5.  Machine learning classifies predictive kinematic features in a mouse model of neurodegeneration.

Authors:  Ruyi Huang; Ali A Nikooyan; Bo Xu; M Selvan Joseph; Hamidreza Ghasemi Damavandi; Nathan von Trotha; Lilian Li; Ashok Bhattarai; Deeba Zadeh; Yeji Seo; Xingquan Liu; Patrick A Truong; Edward H Koo; J C Leiter; Daniel C Lu
Journal:  Sci Rep       Date:  2021-02-17       Impact factor: 4.379

6.  Towards a Mobile Gait Analysis for Patients with a Spinal Cord Injury: A Robust Algorithm Validated for Slow Walking Speeds.

Authors:  Charlotte Werner; Chris Awai Easthope; Armin Curt; László Demkó
Journal:  Sensors (Basel)       Date:  2021-11-06       Impact factor: 3.576

7.  Derivation of the Gait Deviation Index for Spinal Cord Injury.

Authors:  Diana Herrera-Valenzuela; Isabel Sinovas-Alonso; Juan C Moreno; Ángel Gil-Agudo; Antonio J Del-Ama
Journal:  Front Bioeng Biotechnol       Date:  2022-07-06

8.  Normative Data for an Instrumental Assessment of the Upper-Limb Functionality.

Authors:  Marco Caimmi; Eleonora Guanziroli; Matteo Malosio; Nicola Pedrocchi; Federico Vicentini; Lorenzo Molinari Tosatti; Franco Molteni
Journal:  Biomed Res Int       Date:  2015-10-11       Impact factor: 3.411

  8 in total

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