Complexity of postural control in infants: linear and nonlinear features revealed by principal component analysis

Regina T. Harbourne, Joan E. Deffeyes, Anastasia Kyvelidou, Nicholas Stergiou

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

Nonlinear analysis of standing postural control in healthy adults reveals a chaotic structure of the center of pressure time series. Independent sitting is the first controlled posture during development, and can also be examined for nonlinear dynamics. We performed a principal component analysis on variables extracted from the center of pressure (COP) time series of infants sitting independently. Our purpose was to describe factors that could be interpreted for clinical use in evaluating postural control for infants, and determine if nonlinear measures provide additional information about postural control not quantified by standard linear measures. Four factors were identified: the area or amount of postural sway and the overall variability of the sway (linear); the complexity of the sway in the anterior-posterior direction (nonlinear); power variability or velocity (linear); and the complexity of the sway in the medial-lateral direction (nonlinear). Nonlinear measures, which are used to examine complexity in many physiological systems, describe the variability of postural control that is not described by linear measures. Nonlinear measures may be critical in determining the developing health of the postural control system in infants, and may be useful in early diagnosis of movement disorders. The measurement of nonlinear dynamics of postural control reveals a chaotic structure of postural control in infancy, which may be an indicator of healthy postural control throughout development.

Original languageEnglish (US)
Pages (from-to)123-144
Number of pages22
JournalNonlinear Dynamics, Psychology, and Life Sciences
Volume13
Issue number1
StatePublished - Jan 2009

Keywords

  • Complexity
  • Infants
  • Nonlinear
  • Postural control
  • Principal component

ASJC Scopus subject areas

  • Applied Mathematics

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