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Journal articles on the topic 'Clinical Gait Analysis'

Author: Grafiati
Published: 4 June 2021
Last updated: 10 February 2022

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1

Davis, R. B. "Clinical gait analysis." IEEE Engineering in Medicine and Biology Magazine 7, no. 3 (September 1988): 35–40. http://dx.doi.org/10.1109/51.7933.

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2

Davis, Roy B. "Reflections on clinical gait analysis." Journal of Electromyography and Kinesiology 7, no. 4 (December 1997): 251–57. http://dx.doi.org/10.1016/s1050-6411(97)00008-4.

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3

Ellis, Malcolm, and Adrian Howe. "A Clinical Gait Analysis System." Engineering in Medicine 16, no. 4 (October 1987): 217–20. http://dx.doi.org/10.1243/emed_jour_1987_016_049_02.

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A gait analysis system has been devised that is not only relatively inexpensive, but is also quick to use, requires no expertise to run, and does not need any special laboratory facilities. The system monitors the subject's knee and hip movements during ambulation using electro-goniometers. Foot contact data are obtained using lightweight, flexible, foot switches. The data are sent to a computer via an eight channel telemetry system carried by the subject on a waist belt. The software is designed to simplify analysis and be ‘user friendly’. After a simple calibration routine, the system prompts the operator to ask the subject to walk a number of steps. The computer ignores the initial steps taken as these are not typical of normal gait. It then collects data from the consequent steps, averages the data and then displays them in both graphical and numerical form. A patient can be tested and a printout provided for insertion in the patient's notes within ten minutes. Only one hours training is required to learn to operate the system. A patient can be tested in a physiotherapy department, corridor, or in any area where a few consecutive steps can be taken.
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4

Andriacchi, T. P. "Clinical applications of gait analysis." Journal of Biomechanics 26, no. 3 (March 1993): 324. http://dx.doi.org/10.1016/0021-9290(93)90484-v.

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5

Olney, Sandra J. "Clinical information in gait analysis." Journal of Biomechanics 26, no. 3 (March 1993): 325. http://dx.doi.org/10.1016/0021-9290(93)90486-x.

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6

Baumann, J. U. "Requirements of clinical gait analysis." Human Movement Science 10, no. 5 (October 1991): 535–42. http://dx.doi.org/10.1016/0167-9457(91)90042-v.

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7

Whittle, Michael W. "Clinical gait analysis: A review." Human Movement Science 15, no. 3 (June 1996): 369–87. http://dx.doi.org/10.1016/0167-9457(96)00006-1.

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8

Watelain, Éric. "Human gait: From clinical gait analysis to diagnosis assistance." Movement & Sport Sciences 98, no. 4 (2017): 3. http://dx.doi.org/10.3917/sm.098.0003.

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9

Sutherland, D. H. "The evolution of clinical gait analysis." Gait & Posture 16, no. 2 (October 2002): 159–79. http://dx.doi.org/10.1016/s0966-6362(02)00004-8.

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10

Walsh, M. "Gait Analysis – A Paediatric Clinical Perspective." Physiotherapy Practice and Research 32, no. 1 (2011): 24–27. http://dx.doi.org/10.3233/ppr-2011-32105.

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11

Duhamel, A., J. L. Bourriez, P. Devos, P. Krystkowiak, A. Destée, P. Derambure, and L. Defebvre. "Statistical tools for clinical gait analysis." Gait & Posture 20, no. 2 (October 2004): 204–12. http://dx.doi.org/10.1016/j.gaitpost.2003.09.010.

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12

Baker, Richard, and James Robb. "Foot models for clinical gait analysis." Gait & Posture 23, no. 4 (June 2006): 399–400. http://dx.doi.org/10.1016/j.gaitpost.2006.03.005.

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13

Rozendal, R. H. "Clinical gait analysis: Problems and solutions?" Human Movement Science 10, no. 5 (October 1991): 555–64. http://dx.doi.org/10.1016/0167-9457(91)90044-x.

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14

Bruckner, Jan. "The Gait Workshop a practical guide to clinical gait analysis." South African Journal of Physiotherapy 55, no. 3 (August 31, 1999): 24. http://dx.doi.org/10.4102/sajp.v55i3.571.

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15

Viehweger, E., L. Zürcher Pfund, M. Hélix, M. A. Rohon, M. Jacquemier, D. Scavarda, J. L. Jouve, G. Bollini, A. Loundou, and M. C. Simeoni. "Influence of clinical and gait analysis experience on reliability of observational gait analysis (Edinburgh Gait Score Reliability)." Annals of Physical and Rehabilitation Medicine 53, no. 9 (November 2010): 535–46. http://dx.doi.org/10.1016/j.rehab.2010.09.002.

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16

Tu, Binbin, Hui Xu, and Xiaowei Han. "Application of accelerometer-based gait recognition to adjuvant clinical gait analysis." Technology and Health Care 27, no. 6 (November 7, 2019): 603–11. http://dx.doi.org/10.3233/thc-181376.

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17

Bruderer-Hofstetter, M., F. Rast, C. Bauer, E. Graf, and A. Meichtry. "Pattern recognition methods in clinical gait analysis – What do we gain?" Gait & Posture 42 (December 2015): S59. http://dx.doi.org/10.1016/j.gaitpost.2015.03.104.

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18

Kyeong, Sunghyon, Seung Min Kim, Suk Jung, and Dae Hyun Kim. "Gait pattern analysis and clinical subgroup identification." Medicine 99, no. 15 (April 2020): e19555. http://dx.doi.org/10.1097/md.0000000000019555.

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19

Kleissen, R. "Quantitative surface electromyography for clinical gait analysis." Gait & Posture 3, no. 3 (September 1995): 171. http://dx.doi.org/10.1016/0966-6362(95)99071-r.

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20

Hmay, DRW, D. Hynd, DJ Ewins, and SC Hughes. "Clinical gait analysis of hip disarticulation amputees." Gait & Posture 3, no. 3 (September 1995): 175. http://dx.doi.org/10.1016/0966-6362(95)99085-y.

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21

Tirosh, Oren, and Richard Baker. "Gaitabase: New approach to clinical gait analysis." Gait & Posture 24 (December 2006): S52—S53. http://dx.doi.org/10.1016/j.gaitpost.2006.11.038.

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22

Ramakrishnan, Tyagi, Seok Hun Kim, and Kyle B. Reed. "Human Gait Analysis Metric for Gait Retraining." Applied Bionics and Biomechanics 2019 (November 11, 2019): 1–8. http://dx.doi.org/10.1155/2019/1286864.

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The combined gait asymmetry metric (CGAM) provides a method to synthesize human gait motion. The metric is weighted to balance each parameter’s effect by normalizing the data so all parameters are more equally weighted. It is designed to combine spatial, temporal, kinematic, and kinetic gait parameter asymmetries. It can also combine subsets of the different gait parameters to provide a more thorough analysis. The single number quantifying gait could assist robotic rehabilitation methods to optimize the resulting gait patterns. CGAM will help define quantitative thresholds for achievable balanced overall gait asymmetry. The study presented here compares the combined gait parameters with clinical measures such as timed up and go (TUG), six-minute walk test (6MWT), and gait velocity. The comparisons are made on gait data collected on individuals with stroke before and after twelve sessions of rehabilitation. Step length, step time, and swing time showed a strong correlation to CGAM, but the double limb support asymmetry has nearly no correlation with CGAM and ground reaction force asymmetry has a weak correlation. The CGAM scores were moderately correlated with TUG and strongly correlated to 6MWT and gait velocity.
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23

Johanson, Elise M., and Shannon Richards. "The Gait Workbook: A Practical Guide to Clinical Gait Analysis. Bruckner J." Journal of Physical Therapy Education 13, no. 1 (1999): 55–56. http://dx.doi.org/10.1097/00001416-199901000-00018.

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24

Tokita, Takashi, Kyoya Takagi, Shigenori Matsubara, Toshimi Kojima, Hiromichi Shirato, Rikio Murakami, Hirofumi Akagi, Yoshiro Mori, and Yoji Hayano. "Gait analysis in labyrinthine disorders." Equilibrium Research 47, Suppl-3 (1988): 142–48. http://dx.doi.org/10.3757/jser.47.suppl-3_142.

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25

Curran, Sarah A., and Howard J. Dananberg. "Future of Gait Analysis." Journal of the American Podiatric Medical Association 95, no. 2 (March 1, 2005): 130–42. http://dx.doi.org/10.7547/0950130.

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Despite the plethora of information on human gait analysis, its continued use as a clinical tool remains uncertain. Analysis of gait dysfunction has become integral to podiatric medical practice, and, like many specialized fields, it is rapidly changing to meet the needs of the future. Practice in the 21st century is predicated on the concept of multidisciplinary working approaches and a growing trend toward evidence-based practice, in which gait analysis could play a prominent role. This article provides a historical synopsis of instrumented gait analysis and its associated subcomponents and discusses the salient issues concerning its future role in podiatric medicine. (J Am Podiatr Med Assoc 95(2): 130–142, 2005)
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26

Martin, Kathy. "Measuring Walking: A Handbook of Clinical Gait Analysis." Physical & Occupational Therapy In Pediatrics 34, no. 1 (December 30, 2013): 112–13. http://dx.doi.org/10.3109/01942638.2014.873638.

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27

WEEREN, P. R. "The clinical applicability of automated gait analysis systems." Equine Veterinary Journal 34, no. 3 (January 5, 2010): 218–19. http://dx.doi.org/10.2746/042516402776186029.

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28

Nocent, O., D. Trafial, S. Piotin, A. Benassarou, M. Krajecki, F. C. Boyer, and R. Taïar. "New simplified 3D device for clinical gait analysis." Annals of Physical and Rehabilitation Medicine 56 (October 2013): e161. http://dx.doi.org/10.1016/j.rehab.2013.07.343.

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29

Zhao, Song, Yun-su Chen, and Xian-long Zhang. "Clinical application of gait analysis in hip arthroplasty." Orthopaedic Surgery 2, no. 2 (May 2010): 94–99. http://dx.doi.org/10.1111/j.1757-7861.2010.00070.x.

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30

Benedetti, MG, F. Catani, A. Leardini, E. Pignotti, and S. Giannini. "Data management in gait analysis for clinical applications." Clinical Biomechanics 13, no. 3 (April 1998): 204–15. http://dx.doi.org/10.1016/s0268-0033(97)00041-7.

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31

Fuentes-Sanz, Adela, Joaquin Moya-Angeler, Felipe López-Oliva, and Francisco Forriol. "Clinical Outcome and Gait Analysis of Ankle Arthrodesis." Foot & Ankle International 33, no. 10 (October 2012): 819–27. http://dx.doi.org/10.3113/fai.2012.0819.

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32

Harlaar, J., RFM Kleissen, and GL Lankhorst. "Applications of multimedia technology in clinical gait analysis." Gait & Posture 3, no. 3 (September 1995): 173. http://dx.doi.org/10.1016/0966-6362(95)99077-x.

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33

van der Krogt, M., M. Goudriaan, M. Petrarca, A. Balemans, M. Piening, G. Vasco, E. Castelli, K. Desloovere, and J. Harlaar. "A European consensus protocol for clinical gait analysis." Gait & Posture 42 (December 2015): S18. http://dx.doi.org/10.1016/j.gaitpost.2015.03.042.

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34

Kainz, Hans, David Graham, Julie Edwards, Henry P. J. Walsh, Sheanna Maine, Roslyn N. Boyd, David G. Lloyd, Luca Modenese, and Christopher P. Carty. "Reliability of four models for clinical gait analysis." Gait & Posture 54 (May 2017): 325–31. http://dx.doi.org/10.1016/j.gaitpost.2017.04.001.

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35

Saraswat, Prabhav, Michael S. Andersen, and Bruce A. MacWilliams. "A musculoskeletal foot model for clinical gait analysis." Journal of Biomechanics 43, no. 9 (June 2010): 1645–52. http://dx.doi.org/10.1016/j.jbiomech.2010.03.005.

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36

Dierick, Frédéric, Massimo Penta, David Renaut, and Christine Detrembleur. "A force measuring treadmill in clinical gait analysis." Gait & Posture 20, no. 3 (December 2004): 299–303. http://dx.doi.org/10.1016/j.gaitpost.2003.11.001.

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37

Wren, Tishya A. L., George E. Gorton, Sylvia Õunpuu, and Carole A. Tucker. "Efficacy of clinical gait analysis: A systematic review." Gait & Posture 34, no. 2 (June 2011): 149–53. http://dx.doi.org/10.1016/j.gaitpost.2011.03.027.

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38

Selge, Charlotte, Florian Schoeberl, Andreas Zwergal, Georg Nuebling, Thomas Brandt, Marianne Dieterich, Roman Schniepp, and Klaus Jahn. "Gait analysis in PSP and NPH." Neurology 90, no. 12 (February 21, 2018): e1021-e1028. http://dx.doi.org/10.1212/wnl.0000000000005168.

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ObjectiveTo test whether quantitative gait analysis of gait under single- and dual-task conditions can be used for a differential diagnosis of progressive supranuclear palsy (PSP) and idiopathic normal-pressure hydrocephalus (iNPH).MethodsIn this cross-sectional study, temporal and spatial gait parameters were analyzed in 38 patients with PSP (Neurological Disorders and Stroke and Society for Progressive Supranuclear Palsy diagnostic criteria), 27 patients with iNPH (international iNPH guidelines), and 38 healthy controls. A pressure-sensitive carpet was used to examine gait under 5 conditions: single task (preferred, slow, and maximal speed), cognitive dual task (walking with serial 7 subtractions), and motor dual task (walking while carrying a tray).ResultsThe main results were as follows. First, both patients with PSP and those with iNPH exhibited significant gait dysfunction, which was worse in patients with iNPH with a more broad-based gait (p < 0.001). Second, stride time variability was increased in both patient groups, more pronounced in PSP (p = 0.009). Third, cognitive dual task led to a greater reduction of gait velocity in PSP (PSP 34.4% vs iNPH 16.9%, p = 0.002). Motor dual task revealed a dissociation of gait performance: patients with PSP considerably worsened, but patients with iNPH tended to improve.ConclusionPatients with PSP seem to be more sensitive to dual-task perturbations than patients with iNPH. An increased step width and anisotropy of the effect of dual-task conditions (cognitive vs motor) seem to be good diagnostic tools for iNPH.
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39

Gondo, E., A. Hayashi, S. Mikawa, and Y. Irisawa. "Music therapy on gait disturbance and gait analysis for Parkinson's disease using a portable gait rhythmogram." Journal of the Neurological Sciences 405 (October 2019): 294. http://dx.doi.org/10.1016/j.jns.2019.10.1378.

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40

Engsberg, Jack R., Carole Tucker, Sylvia Ounpuu, Tishya A. Wren, Sue Ann Sisto, and Kenton R. Kaufman. "Gait and clinical movement analysis research priorities: 2007 Update from the research committee of the gait and clinical movement analysis society." Gait & Posture 29, no. 2 (February 2009): 169–71. http://dx.doi.org/10.1016/j.gaitpost.2008.11.015.

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41

AKHTARUZZAMAN, MD, AMIR AKRAMIN SHAFIE, and MD RAISUDDIN KHAN. "GAIT ANALYSIS: SYSTEMS, TECHNOLOGIES, AND IMPORTANCE." Journal of Mechanics in Medicine and Biology 16, no. 07 (November 2016): 1630003. http://dx.doi.org/10.1142/s0219519416300039.

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Human gait is the identity of a person's style and quality of life. Reliable cognition of gait properties over time, continuous monitoring, accuracy of evaluation, and proper analysis of human gait characteristics have demonstrated their importance not only in clinical and medical studies, but also in the field of sports, rehabilitation, training, and robotics research. Focusing on walking gait, this study presents an overview on gait mechanisms, common technologies used in gait analysis, and importance of this particular field of research. Firstly, available technologies that involved in gait analysis are briefly introduced in this paper by concentrating on the usability and limitations of the systems. Secondly, key gait parameters and motion characteristics are elucidated from four angles of views; one: gait phases and gait properties; two: center of mass and center of pressure (CoM-CoP) tracking profile; three: Ground Reaction Force (GRF) and impact, and four: muscle activation. Thirdly, the study focuses on the clinical observations of gait patterns in diagnosing gait abnormalities of impaired patients. The presentation also shows the importance of gait analysis in sports to improve performance as well as to avoid risk of injuries of sports personnel. Significance of gait analysis in robotic research is also illustrated in this part where the study focuses on robot assisted systems and its possible applicability in clinical rehabilitation and sports training.
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42

Akahira, Toshizo, and Kiichiro Taguchi. "Gait Analysis at Beginning of Walking." Equilibrium Research 53, Suppl-10 (1994): 62–66. http://dx.doi.org/10.3757/jser.53.suppl-10_62.

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43

Klucken, J., J. Barth, B. Eskofier, and J. Winkler. "Automated gait analysis in Parkinson's disease." Basal Ganglia 3, no. 1 (March 2013): 61. http://dx.doi.org/10.1016/j.baga.2013.01.058.

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44

Schwesig, René, Regina Wegener, Christof Hurschler, Kevin Laudner, and Frank Seehaus. "Intra- and Interobserver Reliability Comparison of Clinical Gait Analysis Data between Two Gait Laboratories." Applied Sciences 10, no. 15 (July 23, 2020): 5068. http://dx.doi.org/10.3390/app10155068.

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Comparing clinical gait analysis (CGA) data between clinical centers is critical in the treatment and rehabilitation progress. However, CGA protocols and system configurations, as well as choice of marker sets and individual variability during marker attachment, may affect the comparability of data. The aim of this study was to evaluate reliability of CGA data collected between two gait analysis laboratories. Three healthy subjects underwent a standardized CGA protocol at two separate centers. Kinematic data were captured using the same motion capturing systems (two systems, same manufacturer, but different analysis software and camera configurations). The CGA data were analyzed by the same two observers for both centers. Interobserver reliability was calculated using single measure intraclass correlation coefficients (ICC). Intraobserver as well as between-laboratory intraobserver reliability were assessed using an average measure ICC. Interobserver reliability for all joints (ICCtotal = 0.79) was found to be significantly lower (p < 0.001) than intraobserver reliability (ICCtotal = 0.93), but significantly higher (p < 0.001) than between-laboratory intraobserver reliability (ICCtotal = 0.55). Data comparison between both centers revealed significant differences for 39% of investigated parameters. Different hardware and software configurations impact CGA data and influence between-laboratory comparisons. Furthermore, lower intra- and interobserver reliability were found for ankle kinematics in comparison to the hip and knee, particularly for interobserver reliability.
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45

Janssen, Maurice, Rianne Pas, Jos Aarts, Yvonne Janssen-Potten, Hans Vles, Christine Nabuurs, Rob van Lummel, Robert Stokroos, and Herman Kingma. "Clinical observational gait analysis to evaluate improvement of balance during gait with vibrotactile biofeedback." Physiotherapy Research International 17, no. 1 (January 5, 2011): 4–11. http://dx.doi.org/10.1002/pri.504.

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46

Gulenc, Baris, Shavkat Kuchimov, and Yener Temelli. "Clinical and gait analysis of isolated soft tissue release surgery in crouch gait patients." Annals of Medical Research 26, no. 8 (2019): 1600. http://dx.doi.org/10.5455/annalsmedres.2019.05.271.

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47

Pontious, J., HJ Hillstrom, T. Monahan, and S. Connelly. "Talonavicular coalition. Objective gait analysis." Journal of the American Podiatric Medical Association 83, no. 7 (July 1, 1993): 379–85. http://dx.doi.org/10.7547/87507315-83-7-379.

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Talonavicular coalitions, a rarely reported fusion between the talus and navicular, are often an incidental radiographic finding that may be asymptomatic or associated with peroneal spasm. The authors present a review of literature and case report based on clinical evaluation and instrumented gait analysis. Specifically, a patient presenting with a bilateral talonavicular coalition was objectively evaluated with kinetic, kinematic, muscle dynamometry, and pedobarographic testing to understand the biomechanical limitations related to this pathology. An excessive passive component of ankle torque, a high first metatarsophangeal joint plantar pressure, and a diminished time in the midstance portion of stance phase were measured and compared to those of healthy individuals.
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48

KUBOTA, Toshio. "A methodology on the clinical application of gait analysis." Japanese Journal of Rehabilitation Medicine 24, no. 4 (1987): 237–51. http://dx.doi.org/10.2490/jjrm1963.24.237.

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49

Yuan, Z., M. E. Harrington, and A. B. Zavatsky. "Hip joint centre position estimation for clinical gait analysis." Journal of Biomechanics 39 (January 2006): S67. http://dx.doi.org/10.1016/s0021-9290(06)83154-4.

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50

&NA;, &NA;. "Kerrigan DC: CLINICAL GAIT ANALYSIS TO IMPROVE REHABILITATION CARE." American Journal of Physical Medicine & Rehabilitation 73, no. 2 (April 1994): 147. http://dx.doi.org/10.1097/00002060-199404000-00042.

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