Literature DB >> 12297257

The evolution of clinical gait analysis. Part II kinematics.

D H Sutherland1.   

Abstract

Kinematics is treated as a single topic in this manuscript and the emphasis is on early history, just as it was in Part I, Electromyography. Needless to say, neither kinematics nor electromyography, nor kinetics and energy (the latter to be included in Part III) are stand-alone components of clinical gait analysis. The only reason for this selective format is that it lessens my task to be able to write about one subject at a time. One of the consequences of this arbitrary separation is that some contributors, who have enriched more than one portion of clinical gait analysis, are highlighted only in the area in which they have contributed the most. I began with Kinesiological Electromyography in Part I because the earliest stirrings of the dream of clinical gait analysis were expressed in the development of KEMG (kinesiological electromyography). The early investigators realized that very little could be said about the dynamic action of muscles without KEMG. Next, in chronological order, came kinematics. I have been an active participant and eyewitness, and take full responsibility for attempting to write an early history at a time when most of the contributors are still alive. Ordinarily, history is written much later, in order to fully grasp the significance of individual contributions in the tapestry of the whole. As stated in Part I, Electromyography, the emphasis has been placed on the early history. The application of motion analysis to sports medicine, and sports medicine functional analysis, is covered only lightly here, and this should not be interpreted as minimizing its importance. The literature on this subject is now quite voluminous and it would not be possible to cover it adequately in this manuscript. Later historical writings may differ significantly and will hopefully give more recognition to pioneers in later generations: those physicians, engineers, physical therapists and kinesiologists who are lifting the level of clinical gait analysis and directing their energies in expanding clinical directions. It is hoped that this manuscript will prompt additional manuscripts, as well as letters to the editor of Gait and Posture on the content of this review paper.

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Mesh:

Year:  2002        PMID: 12297257     DOI: 10.1016/s0966-6362(02)00004-8

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


  19 in total

1.  BioKin: an ambulatory platform for gait kinematic and feature assessment.

Authors:  Samitha W Ekanayake; Andrew J Morris; Mike Forrester; Pubudu N Pathirana
Journal:  Healthc Technol Lett       Date:  2015-02-25

Review 2.  A systematic review of mechanisms of gait speed change post-stroke. Part 2: exercise capacity, muscle activation, kinetics, and kinematics.

Authors:  Elizabeth C Wonsetler; Mark G Bowden
Journal:  Top Stroke Rehabil       Date:  2017-02-20       Impact factor: 2.119

Review 3.  A unified perspective on ankle push-off in human walking.

Authors:  Karl E Zelik; Peter G Adamczyk
Journal:  J Exp Biol       Date:  2016-12-01       Impact factor: 3.312

Review 4.  Current applications of gait analysis after total knee arthroplasty: A scoping review.

Authors:  Neeraj Vij; Christian Leber; Kenneth Schmidt
Journal:  J Clin Orthop Trauma       Date:  2022-09-05

5.  Task constraints and minimization of muscle effort result in a small number of muscle synergies during gait.

Authors:  Friedl De Groote; Ilse Jonkers; Jacques Duysens
Journal:  Front Comput Neurosci       Date:  2014-09-18       Impact factor: 2.380

6.  The influence of insoles with a peroneal pressure point on the electromyographic activity of tibialis anterior and peroneus longus during gait.

Authors:  Oliver Ludwig; Jens Kelm; Michael Fröhlich
Journal:  J Foot Ankle Res       Date:  2016-08-22       Impact factor: 2.303

7.  The effect of subject measurement error on joint kinematics in the conventional gait model: Insights from the open-source pyCGM tool using high performance computing methods.

Authors:  Mathew Schwartz; Philippe C Dixon
Journal:  PLoS One       Date:  2018-01-02       Impact factor: 3.240

8.  Gait analysis methods: an overview of wearable and non-wearable systems, highlighting clinical applications.

Authors:  Alvaro Muro-de-la-Herran; Begonya Garcia-Zapirain; Amaia Mendez-Zorrilla
Journal:  Sensors (Basel)       Date:  2014-02-19       Impact factor: 3.576

9.  Detecting Gait Phases from RGB-D Images Based on Hidden Markov Model.

Authors:  Hamed Heravi; Afshin Ebrahimi; Ehsan Olyaee
Journal:  J Med Signals Sens       Date:  2016 Jul-Sep

10.  What is the Best Configuration of Wearable Sensors to Measure Spatiotemporal Gait Parameters in Children with Cerebral Palsy?

Authors:  Lena Carcreff; Corinna N Gerber; Anisoara Paraschiv-Ionescu; Geraldo De Coulon; Christopher J Newman; Stéphane Armand; Kamiar Aminian
Journal:  Sensors (Basel)       Date:  2018-01-30       Impact factor: 3.576

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