Literature DB >> 8189711

On the measurement of dynamic stability of human locomotion.

Y Hurmuzlu1, C Basdogan.   

Abstract

The main focus of the present investigation is the development of quantitative measures to assess the dynamic stability of human locomotion. The analytical methodology is based on Floquet theory, which was developed to investigate the stability of nonlinear oscillators. Here the basic approach is modified such that it accommodates the study of the complex dynamics of human locomotion and differences among various individuals. A quantitative stability index has been developed to characterize the ability of humans to maintain steady gait patterns. Floquet multipliers of twenty normal subjects were computed from the kinematic data at Poincaré sections taken at four instants of the gait cycle, namely heel strike, foot flat, heel off, and toe off. Then, an averaged stability index was computed for each subject. Statistical analysis was performed to demonstrate the utility of the stability indices as quantitative measures of dynamic stability of gait for the subject population tested during the present study.

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Mesh:

Year:  1994        PMID: 8189711     DOI: 10.1115/1.2895701

Source DB:  PubMed          Journal:  J Biomech Eng        ISSN: 0148-0731            Impact factor:   2.097


  38 in total

1.  Walking dynamics are symmetric (enough).

Authors:  M Mert Ankaralı; Shahin Sefati; Manu S Madhav; Andrew Long; Amy J Bastian; Noah J Cowan
Journal:  J R Soc Interface       Date:  2015-07-06       Impact factor: 4.118

2.  The influence of gait speed on local dynamic stability of walking.

Authors:  Scott A England; Kevin P Granata
Journal:  Gait Posture       Date:  2006-04-18       Impact factor: 2.840

3.  Dynamic stability of human walking in visually and mechanically destabilizing environments.

Authors:  Patricia M McAndrew; Jason M Wilken; Jonathan B Dingwell
Journal:  J Biomech       Date:  2010-11-20       Impact factor: 2.712

Review 4.  Dynamic stability differences in fall-prone and healthy adults.

Authors:  Kevin P Granata; Thurmon E Lockhart
Journal:  J Electromyogr Kinesiol       Date:  2007-08-07       Impact factor: 2.368

Review 5.  Using dynamic walking models to identify factors that contribute to increased risk of falling in older adults.

Authors:  Paulien E Roos; Jonathan B Dingwell
Journal:  Hum Mov Sci       Date:  2013-10-10       Impact factor: 2.161

6.  Influence of neuromuscular noise and walking speed on fall risk and dynamic stability in a 3D dynamic walking model.

Authors:  Paulien E Roos; Jonathan B Dingwell
Journal:  J Biomech       Date:  2013-05-06       Impact factor: 2.712

Review 7.  Human movement variability, nonlinear dynamics, and pathology: is there a connection?

Authors:  Nicholas Stergiou; Leslie M Decker
Journal:  Hum Mov Sci       Date:  2011-07-29       Impact factor: 2.161

8.  Influence of simulated neuromuscular noise on the dynamic stability and fall risk of a 3D dynamic walking model.

Authors:  Paulien E Roos; Jonathan B Dingwell
Journal:  J Biomech       Date:  2011-03-26       Impact factor: 2.712

Review 9.  Movement variability near goal equivalent manifolds: fluctuations, control, and model-based analysis.

Authors:  Joseph P Cusumano; Jonathan B Dingwell
Journal:  Hum Mov Sci       Date:  2013-11-07       Impact factor: 2.161

10.  Dynamic instability during post-stroke hemiparetic walking.

Authors:  Pei-Chun Kao; Jonathan B Dingwell; Jill S Higginson; Stuart Binder-Macleod
Journal:  Gait Posture       Date:  2014-06-04       Impact factor: 2.840

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