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Virginia Tech

Applications of Motor Variability for Assessing Repetitive Occupational Tasks

Abstract

dc:description.abstract

The human body has substantial kinetic and kinematic degrees-of-freedoms, so redundant solutions are available for the central nervous system (CNS) to perform a repetitive task. Due to these redundancies, inherent variations exist in human movement, called motor variability (MV). Current evidence suggests that MV can be beneficial, and that there is an inverse association between MV and risk of injury. To better understand how the CNS manipulates MV to reduce injury risks, we investigated the effects of individual differences, task-relevant aspects, and psychological factors as modifiers of MV. Earlier work found that experienced workers adapted more stable movements than novices in repetitive lifting tasks. To expand on this, we quantified how MV differs between experienced workers and novices in different lifting conditions (i.e., lifting asymmetry and fatigue). Three different measures (cycle-to-cycle SD, sample entropy, and the goal equivalent manifold) were used to quantify MV. In a symmetric lifting task, experienced workers had more constrained movement than novices, and experienced workers exhibited more consistent behavior in the asymmetric condition. Novices constrained their movements, and could not maintain the same level of variability in the asymmetric condition. We concluded that experienced workers adapt stable or flexible strategies depending on task difficulty. In a prolonged lifting task, both groups increased their MV to adapt to fatigue; they particularly increased variability in a direction that had no effects on their main task goal. Developing fatigue also makes it difficult for individuals maintain the main goal. Based on these results, we conclude that increasing variability is an adaptive strategy in response to fatigue. We also assessed variability in gait parameters to compare gait adaptability using a head-worn display (HWD) compared with head-down displays for visual information presentation. An effective strategy we observed for performing a cognitive task successfully during walking was to increase gait variability in the goal direction. In addition, we found that head-up walking had smaller effects on MV, suggesting that HWDs are a promising technology to reduce adverse events during gait (e.g., falls). In summary, these results suggest that MV can be a useful indicator for evaluating some occupational injury risks.

Degree

thesis:*
Name thesis:degree_name
Ph. D.
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Industrial and Systems Engineering
Department dc:contributor.department
Industrial and Systems Engineering
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2017

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Sedighi, Alireza
Chair dc:contributor.committeechair
  • Nussbaum, Maury A.
Committee members dc:contributor.committeemember
  • Kong, Zhenyu
  • Srinivasan, Divya
  • Ross, Shane D.

Subjects

dc:subject × 10

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:10935
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/77947

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Sedighi, Alireza. Applications of Motor Variability for Assessing Repetitive Occupational Tasks. doctoral thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/77947