Non-Linear Modeling of Motor Development in Typically Developing Children and Youth Aged 5–18 Years Using Robot-Based Behavioral Assessments

Clinical tasks are often used to differentiate the motor performance of individuals who have impaired function. However, these are not as accurate and repeatable as robotic tasks. Additionally, motor development occurs rapidly at early ages and slows as they reach adulthood, resulting in a non-linear model of performance. There is also evidence that variability in performance changes as children and youth age. Accurate normative models of performance are necessary to identify deficiencies in motor performance and to track the efficacy of therapies. This work aimed to create normative models of motor development based on robotic assessments in typically developing children and youth. Two hundred and eighty-eight participants who are typically developing (ages 5-18) completed a robotic point-to-point reaching task and an object-hitting task using the Kinarm Exoskeleton. Exponential or quadratic curves were fit to performance parameters generated by Kinarm to model typical performance. These models included a linear term to account for changing variabilities with age. Most performance parameters showed improvement with age, and none showed deterioration. Some parameters showed large changes in variability in performance with age, with up to a 74% decrease in the range of typical performance. Reduced variability occurs with age, indicating the need to account for differences in variability when developing models of typical motor performance in children and youth. The models that are used to identify deficits in motor performance should account for changing variability in data and changing repeatability with age to increase the accuracy of identification of deficits.

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Publication Details

Journal
Bioengineering
Published
2025-11-12
DOI
https://doi.org/10.3390/bioengineering12111240
Citations
1
Primary Topic
Cerebral Palsy and Movement Disorders
Type
article
Field-Weighted Citation Impact
1.47
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article

Non-Linear Modeling of Motor Development in Typically Developing Children and Youth Aged 5–18 Years Using Robot-Based Behavioral Assessments

T. Claire Davies, Stephen H. Scott, Stephan C. D. Dobri
1 citations
Bioengineering
Cerebral Palsy and Movement Disorders
1.47
article

Non-Linear Modeling of Motor Development in Typically Developing Children and Youth Aged 5–18 Years Using Robot-Based Behavioral Assessments

T. Claire Davies, Stephen H. Scott, Stephan C. D. Dobri
article en
1 citations

Abstract

Clinical tasks are often used to differentiate the motor performance of individuals who have impaired function. However, these are not as accurate and repeatable as robotic tasks. Additionally, motor development occurs rapidly at early ages and slows as they reach adulthood, resulting in a non-linear model of performance. There is also evidence that variability in performance changes as children and youth age. Accurate normative models of performance are necessary to identify deficiencies in motor performance and to track the efficacy of therapies. This work aimed to create normative models of motor development based on robotic assessments in typically developing children and youth. Two hundred and eighty-eight participants who are typically developing (ages 5-18) completed a robotic point-to-point reaching task and an object-hitting task using the Kinarm Exoskeleton. Exponential or quadratic curves were fit to performance parameters generated by Kinarm to model typical performance. These models included a linear term to account for changing variabilities with age. Most performance parameters showed improvement with age, and none showed deterioration. Some parameters showed large changes in variability in performance with age, with up to a 74% decrease in the range of typical performance. Reduced variability occurs with age, indicating the need to account for differences in variability when developing models of typical motor performance in children and youth. The models that are used to identify deficits in motor performance should account for changing variability in data and changing repeatability with age to increase the accuracy of identification of deficits.

BioengineeringVol. 12(11)
Queen's University (CA)
Openalex Percentile: Top 14%
Cerebral Palsy and Movement Disorders
1.47
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