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Postural Organization of Gait Initiation for Biomechanical Analysis Using Force Platform Recordings
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A bidirectional model of postural sway using force plate data.

Karla D Bustamante Valles1, Ubong I Udoekwere2, Jason T Long2

  • 1Marquette University, Orthopaedic and Rehabilitation Engineering Center (OREC), 735 N. 17th Street, Suite 105, Milwaukee, WI 53233; Instituto Tecnologico y de Estudios Superiores de Monterrey (ITESM), Chihuahua Campus, Chihuahua, Mexico.

Critical Reviews in Biomedical Engineering
|May 9, 2015
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Summary
This summary is machine-generated.

This study developed a bidirectional postural control model, revealing sensory conditions significantly alter medial-lateral sway but not anterior-posterior sway in healthy adults.

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Area of Science:

  • Biomechanics
  • Human Motor Control
  • Systems Neuroscience

Background:

  • Postural control is crucial for maintaining balance during quiet standing.
  • Previous models focused on anterior-posterior (AP) sway, neglecting medial-lateral (ML) sway.
  • Understanding multi-directional sway is key to identifying postural control deficits.

Purpose of the Study:

  • To expand a previous AP postural control model to incorporate ML sway during quiet standing.
  • To investigate the effects of sensory conditions on postural control strategies.
  • To simulate postural sway using a bidirectional model with Proportional-Integral-Derivative (PID) controllers.

Main Methods:

  • Developed a bidirectional model simulating two decoupled inverted pendulums for AP (ankle strategy) and ML (hip strategy) sway.
  • Collected postural data from 31 healthy participants under eyes closed, eyes open, and visual feedback conditions.
  • Adjusted PID controller parameters in simulations to match experimental sway metrics (p ≤ 0.01).

Main Results:

  • AP sway controller parameters showed no significant changes across sensory conditions.
  • ML sway controller parameters (stiffness, time delay) exhibited significant changes.
  • Experimental ML sway metrics also differed significantly across the three sensory conditions.

Conclusions:

  • The bidirectional model effectively simulates postural sway, highlighting the distinct control mechanisms for AP and ML directions.
  • Sensory manipulation significantly impacts ML postural control, involving adjustments in stiffness and time delay.
  • This multi-sensory evaluation and modeling approach provides insights into postural pathology and control strategies.