Human motor control: Is a subject-specific quantitative assessment of its multiple characteristics possible? A demonstrative application on children motor development

• Published in: Medical engineering & physics Vol. 85; pp. 27 - 34
• Main Authors: Bisi, Maria Cristina, Stagni, Rita
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.11.2020
• Subjects: Dynamics of gait; Motor assessment; Motor control; Motor development; Motor parameters; Wearable sensors; Motor assessment; Dynamics of gait; Motor development; Motor control; Motor parameters; Wearable sensors
• ISSN: 1350-4533; 1873-4030; 1873-4030
• DOI: 10.1016/j.medengphy.2020.09.002

•Motor control determines motor performance in synergy with musculoskeletal system.•A parametric method for subject-specific assessment of motor control is tested.•Testing was performed on 86 primary school children from I and II grade.•Proposed parameter cluster effectively characterised motor competence. In synergy with the musculoskeletal system, motor control is responsible of motor performance, determining joint kinematics and kinetics as related to task and environmental constraints. Multiple metrics have been proposed to quantify motor control from kinematic measures of motion, each index quantifying a different specific aspect, but the characterization of motor control as related to a specific subject or population during the execution of a specific task is still missing. In the present work, the performance of a novel approach for quantitative parametrization of motor control is tested over 86 primary school children: 36 I grade, 50 II grade; 40 females, 46 males. Children were assessed performing natural and tandem gait using 3 inertial measurement units, and gait variability, regularity, and complexity indexes were calculated from gait temporal parameters and trunk acceleration. Standard Test of Motor Competence and Developmental Coordination Disorder Questionnaire were used to assess reference motor competence. The proposed set of parameters allowed to discriminate the level of motor competence as related to age and standardised scales, while differences related to sex resulted negligible. The proposed method can effectively integrate musculoskeletal dynamic models, allowing the parametric characterization of motor control of specific subjects and/or populations.