2015
DOI: 10.1007/s10439-015-1396-2
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Age Effects on Upper Limb Kinematics Assessed by the REAplan Robot in Healthy Subjects Aged 3 to 93 Years

Abstract: Kinematics is recommended for the quantitative assessment of upper limb movements. The aims of this study were to determine the age effects on upper limb kinematics and establish normative values in healthy subjects. Three hundred and seventy healthy subjects, aged 3-93 years, participated in the study. They performed two unidirectional and two geometrical tasks ten consecutive times with the REAplan, a distal effector robotic device that allows upper limb displacements in the horizontal plane. Twenty-six kine… Show more

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Cited by 10 publications
(8 citation statements)
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“…The algorithm fit a quadratic curve model relative to age, and includes dummy coded variables (0 or 1) for sex and handedness. Quadratic age curves were chosen to model typically developing data as they have been successfully used in previous studies to quantify age-related changes to motor function [3]. Changing variability in performance with age was taken into account by fitting a linear model to the absolute value of the residuals.…”
Section: Discussionmentioning
confidence: 99%
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“…The algorithm fit a quadratic curve model relative to age, and includes dummy coded variables (0 or 1) for sex and handedness. Quadratic age curves were chosen to model typically developing data as they have been successfully used in previous studies to quantify age-related changes to motor function [3]. Changing variability in performance with age was taken into account by fitting a linear model to the absolute value of the residuals.…”
Section: Discussionmentioning
confidence: 99%
“…Motor function and coordination develop and improve in a non-linear fashion as children grow; development is initially rapid and slows with age [1][2][3]. Variability in motor function also decreases with age [4][5][6].…”
Section: Introductionmentioning
confidence: 99%
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“…On the first experimental day (D1), the patients/HIs trained their paretic/nondominant UL on a MSkL task with an SAT (CIRCUIT) 20 , 21 that was implemented on a REAplan neurorehabilitation robot 22 , 23 (Axinesis, Wavre, Belgium; used for motor measures: throughout the study, it did not deliver assistance). To quantify motor control within the same environment, they performed a REACHING task on each day.…”
Section: Methodsmentioning
confidence: 99%
“…2,3 Robotic quantification of the adult population is straightforward as motor control parameters across the ages from 30 to 60 years display little variation. 8 To identify pathological differences in motor control, the clinician or researcher can readily compare robotic outcome measures to a general database of members within the typical population. However, as children grow, motor control improves, making it difficult to generalize the parameters associated with each age.…”
Section: Introductionmentioning
confidence: 99%