Development of functional variability during the motor learning process of a complex cyclic movement. (22nd August 2018)

• Record Type: Journal Article
• Authors: Hamacher, Daniel; Zech, Astrid
• Is Part Of: Journal of biomechanics. Volume 77(2018)
• Page Start: 124
• Page End: 130
• Publication Date: 2018-08-22
• Subjects: Functional variability -- Compensatory variability -- Inertial sensor -- Motor learning -- Riding a pedalo; Animal mechanics -- Periodicals; Biomechanics -- Periodicals; Biomechanics -- Periodicals; Mécanique animale -- Périodiques; Biomécanique -- Périodiques; Electronic journals; 571.4305
• DOI: 10.1016/j.jbiomech.2018.07.015
• Languages: English
• ISSNs: 0021-9290

Abstract

Abstract: Traditionally, movement variability is considered an indicator for sensorimotor malfunctioning. However, functional movement variability is also a result of compensation mechanisms e.g. to account for prior movement deviations and is, therefore, crucial for stable movements. The aim of this study was to analyze functional variability during motor learning of a complex cyclic task. Thirteen young participants practised riding a Pedalo® slalom until they were able to complete the task without errors. Since trunk movements are controlled with high priority, we analyzed trunk kinematics as a result parameter. Since lower extremities affect the result parameter, foot, thigh and pelvis kinematics are considered execution parameters. The movement variability for result and execution parameters was determined for the first (poor performance), an intermediate (medium performance) and the last (good performance) training sessions. Furthermore, the variability ratio (execution/result parameter) was calculated as a measure of functional variability. Movement variability of the result parameter decreased significantly with increasing expertise. In contrast, movement variability of all execution parameters increased significantly from measurements representing poor to medium performance. No change from medium to good performance was found. Functional variability increased over time in all execution parameters. Since the movement variability of all execution parameters did not decrease with increasing Pedalo performance, applying a traditional interpretation approach of movement variability would have led to completely wrong conclusions. Possible mechanisms explaining the increased movement variability are discussed. The variability ratio seems to be the only parameter that can reveal improved sensorimotor functioning during all analyzed stages of motor learning.