Exploring the role of task on kinematic variability and assessing consistency in individual responses across repetitive manual tasks

Abstract

To gain a greater understanding of motor variability (MV) as an individual trait, the effect of task type on MV and individual consistency in MV across three tasks was investigated. Twenty participants performed repetitive carrying, lifting, and simulated sawing tasks. MV was assessed using the linear measure of mean point-by-point standard deviation in three-dimensional upper body joint angles. Task type affected MV, where carrying showed higher MV compared to sawing (23–29%) and lifting (12–19%). Furthermore, MV was higher in lifting compared to sawing (12–25%). Poor to moderate individual consistency (ICC = 0.42–0.63) was found across tasks. Task type determined MV and only some support for MV as an individual trait across tasks was found. Based on this work, differences in degrees of freedom afforded by the task influence the opportunity to exploit MV, and possibly individual consistency in MV magnitude is specific to the degrees of freedom afforded by the task.

Practitioner summary: In repetitive tasks, movement variability has been proposed as an individual characteristic independent of task characteristics, where repeaters show consistently low variability, while replacers show consistently high variability. In the current study, only moderate support was demonstrated for variability as a consistent individual characteristic across different manual tasks.

Abbreviation

MV: Motor variability; WRMSDs: Work-related musculoskeletal disorders; DOF: Degrees of freedom; meanSD: Mean standard deviation; SD: Standard deviation; H: Handle (of simulated sawing setup); T: Track (of simulated sawing setup); F: Frame (of simulated sawing setup); ICC: Intraclass correlation; UE: Upper extremity; MMH: Manual material handling; EMG: Electromyography

Keywords:

• Repetitive tasks
• manual tasks
• motor variability
• kinematic variability
• individual consistency

Acknowledgements

The authors acknowledge the help of Andrea DiSalvia, Nathania Chan, Amanda Calford, and Alexandre Mir-Orefice for their assistance in subject recruitment, data collection, and data analysis.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This study was funded by the Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant RGPIN-2018-04483. The funding source was not involved in the study design, decision-making, or writing.