Literature DB >> 29205208

Relationships between walking velocity and distance and the symmetry of temporospatial parameters in chronic post-stroke subjects.

Agnieszka Guzik1, Mariusz Drużbicki1,2, Grzegorz Przysada1,2, Andrzej Kwolek1, Agnieszka Brzozowska-Magoń1, Marek Sobolewski3.   

Abstract

PURPOSE: Subjects with post-stroke hemiparesis frequently present with asymmetric gait patterns. Symmetry, reflecting similarities in temporospatial, kinematic parameters, is an important measure of gait assessment. The study was designed to examine the relationships between asymmetry of temporal, spatial and kinematic gait parameters and walking velocity and distance.
METHODS: Temporospatial and kinematic gait parameters were examined in a group of 50 chronic post-stroke subjects and in a group of 25 healthy controls. Symmetry ratio was calculated for all the parameters. Gait velocity was measured during 10-metre test, the walking distance during 2-Minute Walk Test, and balance during Up and Go Test.
RESULTS: The relationship between stance phase duration symmetry and gait speed was at a moderate level (r = -0.43, p = 0.0173). There was a moderate relationship between swing phase symmetry and walking velocity and distance. The findings did not show a significant correlation between step length symmetry versus gait speed and distance.
CONCLUSIONS: There is a mild relationship between self-selected gait velocity and walking distance versus temporal parameters symmetry. The findings do not confirm a relationship between self-selected gait velocity and walking distance versus spatial and kinematic parameters as well as balance. Likewise, no evidence confirms that asymmetry of temporal, spatial, kinematic gait parameters changes with the age of post-stroke subjects or is related to the length of time from stroke onset. Given the above, gait symmetry may be recognized as an important indicator of the level of gait control in post-stroke patients because it enables unique gait assessment, independent from other parameters.

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Mesh:

Year:  2017        PMID: 29205208

Source DB:  PubMed          Journal:  Acta Bioeng Biomech        ISSN: 1509-409X            Impact factor:   1.073


  4 in total

1.  Clinometric Gait Analysis Using Smart Insoles in Patients With Hemiplegia After Stroke: Pilot Study.

Authors:  Minseok Seo; Myung-Jun Shin; Tae Sung Park; Jong-Hwan Park
Journal:  JMIR Mhealth Uhealth       Date:  2020-09-10       Impact factor: 4.773

2.  Agreement, Reliability, and Concurrent Validity of an Outdoor, Wearable-Based Walk Ratio Assessment in Healthy Adults and Chronic Stroke Survivors.

Authors:  Simone K Huber; Ruud H Knols; Jeremia P O Held; Tom Christen; Eling D de Bruin
Journal:  Front Physiol       Date:  2022-06-20       Impact factor: 4.755

3.  A systematic review of the usefulness of magnetic resonance imaging in predicting the gait ability of stroke patients.

Authors:  Takeshi Imura; Tsubasa Mitsutake; Yuji Iwamoto; Ryo Tanaka
Journal:  Sci Rep       Date:  2021-07-12       Impact factor: 4.379

4.  Predictive simulation of post-stroke gait with functional electrical stimulation.

Authors:  Gilmar F Santos; Eike Jakubowitz; Nicolas Pronost; Thomas Bonis; Christof Hurschler
Journal:  Sci Rep       Date:  2021-11-01       Impact factor: 4.379

  4 in total

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