Knowledge based decision support system to assist work-related risk analysis in musculoskeletal disorder

  • Authors:
  • T. Padma;P. Balasubramanie

  • Affiliations:
  • Department of Computer Applications, Sona College of Technology, Salem 636005, Tamilnadu, India;Department of Computer Science, Kongu Engineering College, Perundurai, Erode 638052, Tamilnadu, India

  • Venue:
  • Knowledge-Based Systems
  • Year:
  • 2009

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Abstract

This paper develops a knowledge based decision support system (KBDSS) that acquires and quantifies the work-related risks on musculoskeletal disorder specifically, shoulder and neck pain (SNP) that is a prevalent pain complaint within the working environment. Quantifying SNP subjective risk factors helps the physician in decision making. The objective involves knowledge acquisition performed through literature analysis, traditional and concept mapping interviews with neurology, orthopedic, psychology and physiotherapy experts to identify risk factors that include mechanical, physical and psychosocial categories. The determination of ranking the relative factor importance has accomplished using analytic hierarchy processing (AHP) analysis. Capturing domain expert (DE) knowledge and quantifying risk factors produce KBDSS.