Literature DB >> 11415804

A new method for evaluating motor control in gait under real-life environmental conditions. Part 2: Gait analysis.

R. Moe-Nilssen1.   

Abstract

OBJECTIVE: The validity of assessing balance in gait by measuring balance in standing is questionable. Better methods for measuring balance during walking are therefore needed.
DESIGN: It is suggested that the individual will demonstrate adequate postural control by moving a reference point near the body centre of mass (CoM) smoothly towards an intentional goal, even though movements of the extremities show variability consistent with a changing environment.
BACKGROUND: In spite of an increased interest in variability as a prerequisite for motor control, gait analysis methods focus, to a large extent, on symmetry and repeatability of movements in stereotyped settings.
METHODS: Acceleration of a reference point over the lumbar spine is registered during walking by a portable, triaxial accelerometry system.
RESULTS: A quadratic relation between acceleration root mean square (RMS) and walking speed is demonstrated, and a second degree polynomial can therefore be computed as a curve estimate, if acceleration RMS representing at least three walking speeds are available.
CONCLUSIONS: The relation between acceleration over a reference point on the trunk and walking speed can be compared between trials and also when walking speeds are self-selected. Calibration procedures and testing of the instrument for precision and accuracy in a mechanical testing jig are described in a companion article. RELEVANCE: This study suggests a new alternative to the traditions of measuring balance in standing and movements of the legs in walking. The method allows balance in gait to be assessed at self-selected speeds in relevant environmental conditions, which may facilitate gait analysis in the clinic and improve the validity of the results.

Year:  1998        PMID: 11415804     DOI: 10.1016/s0268-0033(98)00090-4

Source DB:  PubMed          Journal:  Clin Biomech (Bristol, Avon)        ISSN: 0268-0033            Impact factor:   2.063


  34 in total

1.  Validation of a measure of smoothness of walking.

Authors:  Jennifer S Brach; David McGurl; David Wert; Jessie M Vanswearingen; Subashan Perera; Rakie Cham; Stephanie Studenski
Journal:  J Gerontol A Biol Sci Med Sci       Date:  2010-10-05       Impact factor: 6.053

2.  Wearable pendant device monitoring using new wavelet-based methods shows daily life and laboratory gaits are different.

Authors:  Matthew A D Brodie; Milou J M Coppens; Stephen R Lord; Nigel H Lovell; Yves J Gschwind; Stephen J Redmond; Michael Benjamin Del Rosario; Kejia Wang; Daina L Sturnieks; Michela Persiani; Kim Delbaere
Journal:  Med Biol Eng Comput       Date:  2015-08-06       Impact factor: 2.602

3.  Analysis and decomposition of accelerometric signals of trunk and thigh obtained during the sit-to-stand movement.

Authors:  W G M Janssen; J B J Bussmann; H L D Horemans; H J Stam
Journal:  Med Biol Eng Comput       Date:  2005-03       Impact factor: 2.602

4.  Coordination of head and trunk accelerations during walking.

Authors:  J J Kavanagh; S Morrison; R S Barrett
Journal:  Eur J Appl Physiol       Date:  2005-04-13       Impact factor: 3.078

5.  The role of the neck and trunk in facilitating head stability during walking.

Authors:  Justin Kavanagh; Rod Barrett; Steven Morrison
Journal:  Exp Brain Res       Date:  2006-02-18       Impact factor: 1.972

6.  Role of visual input in the control of dynamic balance: variability and instability of gait in treadmill walking while blindfolded.

Authors:  Fabienne Reynard; Philippe Terrier
Journal:  Exp Brain Res       Date:  2014-12-23       Impact factor: 1.972

7.  Bracing of the trunk and neck has a differential effect on head control during gait.

Authors:  S Morrison; D M Russell; K Kelleran; M L Walker
Journal:  J Neurophysiol       Date:  2015-07-15       Impact factor: 2.714

8.  Accelerometry reveals differences in gait variability between patients with multiple sclerosis and healthy controls.

Authors:  Jessie M Huisinga; Martina Mancini; Rebecca J St George; Fay B Horak
Journal:  Ann Biomed Eng       Date:  2012-11-18       Impact factor: 3.934

9.  Three-dimensional assessment of postural tremor during goal-directed aiming.

Authors:  K J Kelleran; S Morrison; D M Russell
Journal:  Exp Brain Res       Date:  2016-07-22       Impact factor: 1.972

10.  High resolution MEMS accelerometers to estimate VO2 and compare running mechanics between highly trained inter-collegiate and untrained runners.

Authors:  Stephen J McGregor; Michael A Busa; James A Yaggie; Erik M Bollt
Journal:  PLoS One       Date:  2009-10-06       Impact factor: 3.240

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