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

Authors:
Diyar Akay;M. Ali Akcayol;Mustafa Kurt
Affiliations:
Department of Industrial Engineering, Gazi University, Maltepe, 06570 Ankara, Turkey;Department of Computer Engineering, Gazi University, Maltepe, 06570 Ankara, Turkey;Department of Industrial Engineering, Gazi University, Maltepe, 06570 Ankara, Turkey
Venue:
Expert Systems with Applications: An International Journal
Year:
2008

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Classifying the risk of work related low back disorders due to manual material handling tasks

Expert Systems with Applications: An International Journal

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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.