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Related Experiment Video

Updated: May 7, 2026

Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb
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Data processing costs for three posture assessment methods.

Catherine Trask1, Svend Erik Mathiassen, Jennie Jackson

  • 1Centre for Musculoskeletal Research, Department of Occupational and Public Health Sciences, University of Gävle, SE - 801 76 Gävle, Sweden. catherine.trask@usask.ca.

BMC Medical Research Methodology
|October 15, 2013
PubMed
Summary

Data processing costs for posture assessment methods vary significantly, with video observation being most expensive. Cost-efficient study designs can be identified using this cost-tracking model.

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Area of Science:

  • Occupational health
  • Ergonomics
  • Research methodology

Background:

  • Data processing represents a significant research cost, yet is often undocumented.
  • This study addresses the need for cost documentation in research by analyzing data processing expenses.

Purpose of the Study:

  • To develop and apply a cost model for data processing in posture assessment research.
  • To compare the data processing costs of self-report, video observation, and inclinometry methods.
  • To simulate the impact of study design on overall processing costs.

Main Methods:

  • A priori cost tracking was used for three posture assessment methods over 80 working days.
  • A cost model was developed with fixed and variable components for the data processing phase.
  • Simulations were run to explore the effects of altering study design parameters on costs.

Main Results:

  • Video observation incurred the highest data processing costs (€30,630), followed by inclinometry (€26,255), and self-report (€12,491).
  • Simulations demonstrated that adjusting design strategies, including software development, training, and sampling frequency, significantly impacts processing costs.
  • Combining data collection and processing costs reduced the cost difference between video and inclinometry, with potential for reversal at larger sample sizes.

Conclusions:

  • The developed data processing cost model complements existing data collection cost models.
  • These models enable evidence-based study planning and the identification of cost-effective research designs.
  • Understanding and modeling data processing costs is crucial for efficient research planning in ergonomics and occupational health.