Literature DB >> 11369268

Reflections on clinical gait analysis.

R B. Davis1.   

Abstract

Clinical gait analysis allows the measurement and assessment of walking biomechanics, which facilitates the identification of abnormal characteristics and the recommendation of treatment alternatives. The predominant methods for this analysis currently include the tracking of external markers placed on the patient, the monitoring of patient/ground interaction (e.g. ground reaction forces), and the recording of muscle electromyographic (EMG) activity, all during gait. These data allow the computation of stride and temporal parameters, joint/segment kinematics, joint kinetics, and EMG plots that are used to gain a better understanding of a patient's walking difficulties. Gait interpretation involves a systemic evaluation of each of these types of data, noting both corroborating and conflicting information while identifying functionally significant deviations from the normal. Understanding the etiology of these abnormalities allows the formulation of a treatment plan that may involve physical therapy, bracing, and/or surgery. This process is challenging because of the complexity of the motion, neuromuscular involvement of the patient (e.g. dynamic spasticity), variability of treatment outcome, and on occasion, uncertainty about the quality of the gait data. The experience of the interpretation team with respect to gait biomechanics, a particular patient population, and the effectiveness of different treatment modalities is the principal determinant of the success of this approach. The clinical gait analysis process continues to evolve positively. It has become more comprehensive and meaningful because of an improved understanding of normal gait biomechanics and more rigorous data collection/reduction protocols that complement accumulated clinically relevant experience.

Entities:  

Year:  1997        PMID: 11369268     DOI: 10.1016/s1050-6411(97)00008-4

Source DB:  PubMed          Journal:  J Electromyogr Kinesiol        ISSN: 1050-6411            Impact factor:   2.368


  11 in total

1.  Gait analysis of walking before and after medial opening wedge high tibial osteotomy.

Authors:  Martin Lind; Jodie McClelland; Joanne E Wittwer; Timothy S Whitehead; Julian A Feller; Kate E Webster
Journal:  Knee Surg Sports Traumatol Arthrosc       Date:  2011-04-12       Impact factor: 4.342

2.  Gait characteristics in a canine model of X-linked myotubular myopathy.

Authors:  Melissa A Goddard; Emily Burlingame; Alan H Beggs; Anna Buj-Bello; Martin K Childers; Anthony P Marsh; Valerie E Kelly
Journal:  J Neurol Sci       Date:  2014-08-29       Impact factor: 3.181

3.  Healthy humans use sex-specific co-ordination patterns of trunk muscles during gait.

Authors:  C Anders; H Wagner; C Puta; R Grassme; H C Scholle
Journal:  Eur J Appl Physiol       Date:  2008-11-21       Impact factor: 3.078

4.  Managing variability in the summary and comparison of gait data.

Authors:  Tom Chau; Scott Young; Sue Redekop
Journal:  J Neuroeng Rehabil       Date:  2005-07-29       Impact factor: 4.262

5.  Gait analysis in children with cerebral palsy.

Authors:  Stéphane Armand; Geraldo Decoulon; Alice Bonnefoy-Mazure
Journal:  EFORT Open Rev       Date:  2016-12-22

Review 6.  Knee Joint Biomechanical Gait Data Classification for Knee Pathology Assessment: A Literature Review.

Authors:  Mariem Abid; Neila Mezghani; Amar Mitiche
Journal:  Appl Bionics Biomech       Date:  2019-05-14       Impact factor: 1.781

7.  Acceleration Gait Measures as Proxies for Motor Skill of Walking: A Narrative Review.

Authors:  Pritika Dasgupta; Jessie VanSwearingen; Alan Godfrey; Mark Redfern; Manuel Montero-Odasso; Ervin Sejdic
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2021-03-01       Impact factor: 3.802

8.  Spatio-temporal parameters and intralimb coordination patterns describing hemiparetic locomotion at controlled speed.

Authors:  Lucio A Rinaldi; Vito Monaco
Journal:  J Neuroeng Rehabil       Date:  2013-06-12       Impact factor: 4.262

9.  Knee joint dysfunctions that influence gait in cerebrovascular injury.

Authors:  Paulo Roberto Garcia Lucareli; Julia Maria D'Andrea Greve
Journal:  Clinics (Sao Paulo)       Date:  2008-08       Impact factor: 2.365

10.  Interrater and intrarater reliability and minimal detectable change of the Wisconsin Gait Scale when used to examine videotaped gait in individuals post-stroke.

Authors:  Robert Wellmon; Amy Degano; Joseph A Rubertone; Sandra Campbell; Kelly A Russo
Journal:  Arch Physiother       Date:  2015-10-05
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