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Related Experiment Video

Updated: Nov 11, 2025

Experimental Methods to Study Human Postural Control
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Identifying human postural dynamics and control from unperturbed balance.

Jongwoo Lee1, Kuangen Zhang2,3,4, Neville Hogan2,5

  • 1Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA. jw127@mit.edu.

Journal of Neuroengineering and Rehabilitation
|March 23, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces a novel mathematical method to accurately identify human balance dynamics without external disturbances. This approach enables better understanding and potential treatment of balance impairments.

Keywords:
Human quiet standingPostural dynamics and controlSystem identificationUnperturbed balance

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Area of Science:

  • Biomechanics
  • Systems Biology
  • Control Theory

Background:

  • Upright standing is a complex motor control task challenged by biological noise.
  • Traditional system identification methods struggle with unperturbed balance due to inaccessible noise processes.
  • Previous studies focused on behavioral patterns rather than underlying control strategies in unperturbed balance.

Purpose of the Study:

  • To present a mathematically rigorous system identification method for analyzing unperturbed human balance dynamics and control.
  • To identify system dynamics in the presence of unknown noise processes without needing noise strength information.
  • To enable the study of balance control strategies without external perturbations.

Main Methods:

  • Developed a system identification method based on autocorrelation matrices with non-zero time lags.
  • Applied the method to identify the system matrix of a discrete-time dynamic system.
  • Validated the method numerically using a simulation model of human upright balancing.

Main Results:

  • The new method accurately identifies the dynamics of human upright balancing.
  • Performance is consistent across various internal and measurement noise strengths, even with substantial measurement noise.
  • Successfully identified a state feedback controller using biomechanically relevant variables.

Conclusions:

  • A new method allows accurate identification of human standing dynamics without external perturbations.
  • The method avoids issues related to adaptation or reflex responses from external stimuli.
  • Potential applications include diagnosing balance disorders and developing assistive/rehabilitative technologies.