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    Nonlinear metrics assessing motor variability in a standardized pipetting task: Between- and within-subject variance components

    Access Status
    Fulltext not available
    Authors
    Samani, A.
    Srinivasan, D.
    Mathiassen, Svend
    Madeleine, P.
    Date
    2015
    Type
    Journal Article
    
    Metadata
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    Citation
    Samani, A. and Srinivasan, D. and Mathiassen, S. and Madeleine, P. 2015. Nonlinear metrics assessing motor variability in a standardized pipetting task: Between- and within-subject variance components. Journal of Electromyography and Kinesiology. 25 (3): pp. 557-564.
    Source Title
    Journal of Electromyography and Kinesiology
    DOI
    10.1016/j.jelekin.2015.01.005
    ISSN
    1050-6411
    School
    School of Physiotherapy and Exercise Science
    URI
    http://hdl.handle.net/20.500.11937/69094
    Collection
    • Curtin Research Publications
    Abstract

    © 2015 Elsevier Ltd. The aim of this study was to estimate the between days test-retest reliability of nonlinear metrics used to quantify motor variability in a repetitive pipetting task. On three separate days, 14 healthy subjects performed pipetting as a general model of repetitive tasks. The task consisted of transferring liquid 20 times with a cycle time of 2.8. s from a pickup tube to eight target tubes placed on a table in front of the subjects. The motion of hand, arm and the pipette tip was tracked in 3D and the shoulder elevation and elbow flexion angle were obtained. Motor variability was assessed using nonlinear metrics based on information theory and recurrence quantification analysis. Between- and within- (between-days) subject variance components were computed using a one-way random effect model, and intra-class correlation coefficients (ICC) were calculated from the variance components as standardized measures of reliability. Most of the metrics displayed a considerable between-days variance component and therefore the ICC showed a slight to moderate reliability. The reported data on between- and within-subject variability can be used to design future studies using nonlinear motor variability metrics on kinematics data.

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