NEFCLASS based extraction of fuzzy rules and classification of risks of low back disorders


AKAY D. , AKCAYOL M. A. , KURT M.

EXPERT SYSTEMS WITH APPLICATIONS, vol.35, no.4, pp.2107-2112, 2008 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 35 Issue: 4
  • Publication Date: 2008
  • Doi Number: 10.1016/j.eswa.2007.09.029
  • Title of Journal : EXPERT SYSTEMS WITH APPLICATIONS
  • Page Numbers: pp.2107-2112

Abstract

In spite of the advanced technology, manual material handling tasks are done frequently and the incidence rate of low back disorders is still high. Classification of industrial jobs related to low back disorder risks has therefore great potential to prevent injuries. In this study, industrial jobs have been classified into two categories as "low risk" and "high risk" using neuro-fuzzy classification. Neuro-fuzzy classification has obtained better results than previous studies which used the same experimental data. Furthermore, "IF-THEN" type fuzzy rules have been extracted easily from the results to analyze potential risk factors. Ergonomic interventions can be done by means of the obtained rules for future reduction in back injuries. (C) 2007 Elsevier Ltd. All rights reserved.