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Updated: Sep 13, 2025

Quantitative Static and Dynamic Assessment of Balance Control in Stroke Patients
Published on: May 17, 2020
Exploring the relationship between static and dynamic balance performance through the same center-of-pressure
A Rizzato1, A Paoli1, Giuseppe Marcolin2
1Department of Biomedical Sciences, University of Padova, Via Marzolo, 3, Padua, 35131, Italy.
Background:
The interpretation of evidence on the relationship between static and dynamic balance is complicated due to the several systems involved in postural control and the heterogeneity of the dynamic balance tasks used. The primary aim of this study was to explore the correlation between static and dynamic balance performance among healthy adults by means of the same center-of-pressure parameters. Given the importance of rapid reactive postural response in dynamic conditions, the secondary aim was to explore the relationship between dynamic balance performance and quadriceps strength and power.
Methods:
Thirty-two healthy subjects (18 females; mean ± SD: age = 30.68 ± 13.31 years; body mass = 74.84 ± 15.18 kg; height = 1.75 ± 0.07 m) were assessed in static and dynamic balance conditions through a force plate that allowed computing the center of pressure trajectory. Static balance was assessed during an upright standing test and dynamic balance during an unstable board test. The same center-of-pressure parameters were calculated for both the two balance conditions: the 95th percentile ellipse area (Area95) and center-of-pressure mean velocity (MeanVelocity). The isometric quadriceps strength of the dominant leg was measured at 90 degrees of knee flexion with a load cell in steady and ballistic conditions. The maximal isometric strength and rate of force development were calculated.
Results:
Pearson's correlation showed non-statistically significant correlations between static and dynamic balance performance for both Area95 (R2 = 0.10; p = 0.07) and MeanVelocity (R2 = 0.001; p = 0.99). Across all parameters, the stepwise multiple linear regression analysis identified the RFD in the 100-150 ms window as the only determinant factor of the Area95 (p < 0.05, adjusted R² = 0.136) and MeanVelocity (p < 0.05, adjusted R² = 0.188) in the dynamic balance condition.
Conclusions:
This study suggests a lack of correlation between static and dynamic balance performance in healthy adults, indicating that both may need to be considered in balance assessments for a more comprehensive evaluation.
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