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Updated: Jul 25, 2026
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Computerized Dynamic Posturography for Postural Control Assessment in Patients with Intermittent Claudication
Published on: December 11, 2013
Disentangling stability and flexibility degrees in Parkinson's disease using a computational postural control model.
Zahra Rahmati1,2, Alfred C Schouten3,4, Saeed Behzadipour5,6
1Mechanical Engineering Department, Sharif University of Technology, Tehran, Iran.
Journal of Neuroengineering and Rehabilitation
|August 16, 2019
Summary
Balance training improved postural control in Parkinson's disease (PD) patients by enhancing sway velocity and stability. This study quantifies neurophysiological improvements, offering a framework for personalized PD therapies.
Area of Science:
- Neuroscience
- Biomedical Engineering
- Rehabilitation Science
Background:
- Parkinson's disease (PD) significantly impairs postural control, reducing quality of life.
- Balance training enhances mobility and stability in PD, but underlying neurophysiological mechanisms require quantitative investigation.
- Lack of patient-specific therapies stems from limited understanding of balance training's effects on PD neurophysiology.
Purpose of the Study:
- To quantitatively evaluate the neurophysiological effects of a balance-training program on postural control in Parkinson's disease patients.
- To utilize a postural control model to analyze posturography data and identify mechanisms of improvement.
- To establish a framework for developing personalized therapies for impaired postural control in PD.
Main Methods:
- Collected center-of-pressure (COP) data from 40 PD patients and 20 controls across various tasks and surfaces (rigid and foam).
- Administered a 12-session balance-training program to PD patients, assessing changes pre- and post-intervention.
- Fitted a postural control model (neuromuscular controller, time delay, internal disturbance torque gain) to posturography data.
Main Results:
- Pre-training, PD patients showed slower COP velocity and lower internal torque gain (due to axial rigidity) and poor foam stability with higher sway amplitude (due to lower control parameters and higher time delay).
- Post-training, balance training improved functional balance and mobility scores.
- Improvements included enhanced sway velocity ('flexibility') and increased control parameters ('stability degree'), leading to quicker responses in unstable conditions.
Conclusions:
- Posturography measures, when analyzed with a postural control model, offer a quantitative framework to understand neurophysiological factors in PD.
- The study elucidates distinct recovery mechanisms following balance training in Parkinson's disease.
- This quantitative approach facilitates the development of tailored therapeutic strategies for individuals with impaired postural control in PD.
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