Between- and within-subject variance of motor variability metrics in females performing repetitive upper-extremity precision work

Kinematic motor variability is extensively studied in occupational, clinical and sports biomechanics, but the consistency of most motor variability metrics have never been reported. In this study, fourteen subjects performed a repetitive pipetting task on three separate days. Movements of hand, arm...

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Veröffentlicht in:Journal of electromyography and kinesiology Jg. 25; H. 1; S. 121 - 129
Hauptverfasser: Srinivasan, Divya, Rudolfsson, Thomas, Mathiassen, Svend Erik
Format: Journal Article
Sprache:Englisch
Veröffentlicht: England Elsevier Ltd 01.02.2015
Schlagworte:
Adult
Analysis of Variance
Biomechanical Phenomena
Female
Humans
Kinematics reliability
Movement
Movement variability
Muscle Contraction
Muscle, Skeletal - physiology
Physical Medicine and Rehabilitation
Pipetting
Precision motor control
Range of Motion, Articular
Repetitive work
Upper Extremity - physiology
Kinematics reliability
Precision motor control
Repetitive work
Movement variability
Pipetting
ISSN:1050-6411, 1873-5711, 1873-5711
Online-Zugang:Volltext
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Zusammenfassung:Kinematic motor variability is extensively studied in occupational, clinical and sports biomechanics, but the consistency of most motor variability metrics have never been reported. In this study, fourteen subjects performed a repetitive pipetting task on three separate days. Movements of hand, arm and pipette tip were recorded in 3D and used to compute shoulder elevation, elbow flexion and shoulder-arm coordination angles, as well as pipette-tip endpoint precision. Cycle-to-cycle motor variability was quantified using linear dispersion measures of standard kinematics properties such as peak velocity, range of motion, and inter-segmental relative phase. Between- and within-subject consistencies of these variability metrics were quantified by variance components estimated using a nested random effects model. For most metrics, the variance between subjects was larger than that between days and cycles. Entering the variance components in statistical power equations showed that for most metrics, a total of 80–100 subjects will be required to detect a 20% difference between two groups with sufficient power, while this difference can typically be detected in repeated-measures (paired) designs using 25 subjects. The reported between and within-subject variance components can be used as a data base to facilitate efficient designs of future studies of kinematic motor variability.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1050-6411
1873-5711
1873-5711
DOI:10.1016/j.jelekin.2014.10.011