Regression analysis of gait parameters with speed in normal children walking at self-selected speeds

B.W. Stansfield, S.J. Hillman, M.E. Hazelwood, J.E. Robb

    Research output: Contribution to journalArticle

    94 Citations (Scopus)

    Abstract

    Dimensionless analysis ensures that differences in sizes (e.g. height and weight) of children have a minimal influence on gait parameters. The results of changes in speed on gait parameters were examined using dimensionless analysis on data from a prospective 5-year study of 16 children. Linear regression analysis of peak and trough values of temporal distance parameters, ground reaction forces, joint angles, moments and powers provide a quantitative description of gait development with normalised speed. These linear relationships can be used to estimate gait parameters from speed measurements for normal subjects. However, caution is advised in using the data to attempt to predict an individual's gait parameters due to the wide spread of data about the regression lines and we do not recommend that the data be used to extrapolate the regression data to wider speed ranges.
    LanguageEnglish
    Pages288-294
    Number of pages6
    JournalGait and Posture
    Volume23
    Issue number3
    DOIs
    Publication statusPublished - 2006

    Fingerprint

    Gait
    Walking
    Regression Analysis
    Linear Models
    Joints
    Weights and Measures
    Walking Speed

    Keywords

    • walking
    • children
    • regression
    • kinematics
    • kinetics
    • bioengineering

    Cite this

    Stansfield, B.W. ; Hillman, S.J. ; Hazelwood, M.E. ; Robb, J.E. / Regression analysis of gait parameters with speed in normal children walking at self-selected speeds. In: Gait and Posture. 2006 ; Vol. 23, No. 3. pp. 288-294.
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    Regression analysis of gait parameters with speed in normal children walking at self-selected speeds. / Stansfield, B.W.; Hillman, S.J.; Hazelwood, M.E.; Robb, J.E.

    In: Gait and Posture, Vol. 23, No. 3, 2006, p. 288-294.

    Research output: Contribution to journalArticle

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