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Updated: Jul 15, 2026
Computerized Dynamic Posturography for Postural Control Assessment in Patients with Intermittent Claudication
Published on: December 11, 2013
Comparative analysis of static and dynamic postural balance control in multiple system atrophy and Parkinson's
Wei Bao1, Kai Chen1, Yuchen Yang2
1School of Mechanical Engineering, Hangzhou Dianzi University, Hangzhou, Zhejiang, China.
Background:
Parkinson's disease (PD) and multiple system atrophy (MSA) are both characterized by postural instability, increasing the risk of falls and impairing quality of life. This study aimed to compare intermittent control strategies between PD and MSA during static and dynamic standing, focusing on changes in active controller parameters that simulate central nervous system (CNS) responses.
Method:
Postural stability was evaluated in 17 healthy controls, 61 PD patients, 40 MSA-C (cerebellar type) patients, and 26 MSA-P (parkinsonian type) patients using an intermittent control model under static and dynamic conditions. Center of pressure (COP) characteristics-including path length, velocity, and trajectory distribution area-were analyzed alongside model parameters such as intermittent switching frequency (reflecting CNS decision-making) and trajectory variability.
Results:
No significant group differences in COP or model parameters were found during static standing. Under dynamic conditions requiring real-time postural adjustments, significant differences emerged between controls and MSA, as well as between PD and both MSA subtypes. The MSA groups exhibited higher intermittent switching frequencies than PD, indicating distinct CNS control strategies. Intermittent switching frequency was negatively correlated with clinical balance scores (rho = -0.6, P < 0.050), suggesting that higher switching rates are associated with better balance performance.
Conclusion:
Dynamic standing tasks reveal distinct postural control strategies in PD and MSA, with MSA showing higher switching frequencies. These findings provide quantitative evidence for differentiating balance control features among neurodegenerative diseases and may inform targeted rehabilitation approaches.
