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Related Concept Videos

Variability: Analysis01:11

Variability: Analysis

Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...

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3D Kinematic Gait Analysis for Preclinical Studies in Rodents
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Quantifying variability in phase portraits: application to gait ontogeny.

John D Polk1, Jesse Spencer-Smith, Louis DiBerardino

  • 1Department of Anthropology, University of Illinois Urbana-Champaign, 109 Davenport Hall, 607 South Mathews Avenue, Urbana, IL, 61801, United States. jdpolk@uiuc.edu

Infant Behavior & Development
|December 1, 2007
PubMed
Summary

New methods quantify gait variation in children. While individual differences are significant, walking patterns stabilize after six months of development.

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Area of Science:

  • Biomechanics
  • Developmental science
  • Dynamical systems theory

Background:

  • Understanding human locomotion development is crucial for identifying developmental milestones and potential issues.
  • Previous studies have explored intralimb coordination during early walking using dynamical systems approaches.
  • Quantifying variability in these complex movement patterns presents analytical challenges.

Purpose of the Study:

  • To introduce novel Fourier- and shape-based analytical methods for quantifying variations in phase-portraits of human gait.
  • To re-analyze existing longitudinal data on infant gait development to assess individual and developmental variability.
  • To determine the point at which gait patterns become stable during the first year of independent walking.

Main Methods:

  • Development of new Fourier-transform based techniques for analyzing kinematic data.
  • Application of shape-based analysis to quantify variations in phase-portraits.
  • Re-analysis of longitudinal intralimb coordination data from infants during their first year of walking.

Main Results:

  • Significant inter-individual variability in gait patterns was observed during early development.
  • Phase-portrait analysis revealed substantial changes in coordination through the ontogenetic period.
  • Gait patterns demonstrated a trend towards stabilization after approximately six months of independent walking.

Conclusions:

  • The novel Fourier- and shape-based methods provide powerful tools for quantifying complex motor variability.
  • Early walking development is characterized by considerable individual differences and dynamic changes.
  • Motor control systems exhibit a capacity for stabilization and pattern refinement within the first year of walking.