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Updated: Jul 25, 2026

Methods to Quantify Pharmacologically Induced Alterations in Motor Function in Human Incomplete SCI
Published on: April 18, 2011
Is dynamic motor control clinically important for identifying gait deviations in individuals with cerebral palsy?
Gilad Sorek1, Marije Goudriaan2, Itai Schurr3
1Laboratory for Paediatric Motion Analysis and Biofeedback Rehabilitation, ALYN Paediatric and Adolescent Rehabilitation Research Centre (Helmsley PARC), Jerusalem, Israel.
Introduction:
Individuals with cerebral palsy (CP) often present with altered motor control. This can be assessed selectively during sitting/lying with the Selective Control Assessment of the Lower Extremity (SCALE), or dynamically with the dynamic motor control index during walking (walk-DMC). Both approaches suggest that altered selective motor control relate to larger gait deviations.
Research Question:
Does the walk-DMC provide valuable information in addition to the SCALE for estimating gait deviations in individuals with CP.
Methods:
Retrospective, treadmill-based gait analysis data of 157 children with spastic CP (mean 11.4±3.5 years) and Gross Motor Function Classification System levels I (n=45), II (n=88) or III (n=24) were extracted. Gait kinematic deviations were evaluated using the Gait Profile Score (GPS). The SCALE, walk-DMC and GPS were extracted for the more clinically involved leg (unilateral-analysis), and for both legs together (bilateral-analysis).
Results:
GPS moderately correlated with both SCALE and walk-DMC scores, unilaterally and bilaterally (r≥0.4; p<0.001). Multivariate linear regression analyses were conducted, taking into account potential confounding factors. In the unilateral analysis, 54% of the GPS variance was explained (p<0.001), with both walk-DMC and SCALE significantly contributing to the GPS variance (p=0.006 and p=0.008, respectively). In the bilateral analysis, 61% of the GPS variance was explained (p<0.001), with both walk-DMC and SCALE significantly contributing to the GPS variance (p=0.006 and p<0.001, respectively). Dimensionless walking speed and use of assistive devices were the only confounding factors included in each analysis.
Significance:
Both SCALE and walk-DMC significantly contribute to GPS variance, suggesting that they likely measure different components of motor control, and both may be useful in understanding the underlying relationship between motor control and deviations in gait kinematics.
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