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Related Experiment Video

Updated: Jul 17, 2026

Experimental Methods to Study Human Postural Control

Experimental Methods to Study Human Postural Control

Published on: September 11, 2019

Application of nonlinear dynamics to human postural control system.

J Han¹, Z Moussavi, T Szturm

¹Department of Electrical and Computer Engineering, University of Manitoba, Winnipeg, Manitoba, Canada. jhan@ee.umanitoba.ca.

Conference Proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference

|February 7, 2007

Summary

Nonlinear dynamics, specifically Rényi fractal dimension, can identify balance disorders in older adults by analyzing postural sway. This method offers insights into balance control distinct from traditional linear measures.

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Experimental Methods to Study Human Postural Control

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Published on: April 12, 2016

Area of Science:

Biomechanics and Motor Control
Rehabilitation Science
Nonlinear Dynamics

Background:

Falls and associated injuries are significant issues for the elderly and individuals with chronic disabilities.
Accurate screening tools for balance performance and fall risk are crucial for health professionals and researchers.
Linear modeling of human physiological systems, like postural control, is often insufficient due to complexity.

Purpose of the Study:

To investigate the application of nonlinear dynamic tools for extracting characteristic features of postural sway.
To compare nonlinear descriptors (Rényi fractal dimension, Rényi spectrum) with linear measures (sway path) for classifying balance disorders.

Main Methods:

Recorded center of foot pressure (COP) trajectories during quiet standing tasks of increasing difficulty.
Utilized Rényi fractal dimension and Rényi spectrum as nonlinear quantitative descriptors of COP data.
Compared nonlinear parameters with the linear sway path in young healthy adults versus elderly individuals with balance impairment.

Main Results:

Rényi fractal dimension and sway path demonstrated potential as classifiers for balance disorders.
Nonlinear and linear parameters provided distinct insights into postural control system characteristics.
Differences were observed between young healthy subjects and elderly patients with balance impairment across task demands.

Conclusions:

Nonlinear dynamic analysis, particularly Rényi fractal dimension, shows promise for assessing balance and fall risk.
COP trajectory analysis using nonlinear methods offers a more nuanced understanding of postural control than linear measures alone.
These findings support the development of advanced screening tools for balance disorders in clinical and research settings.