A Fuzzy Neural Approach to Classifying Low Back Disorders Risks

Classification of low back disorders (LBDs) risks for common industrial lifting jobs is important to control and prevention of this common disability. Of particular interest to the researchers is the use of data mining methods in risk classification. This paper presents an adaptive neuro-fuzzy inference system (ANFIS) model for classifying LBDs risks. Though neuro-fuzzy inference modeling is extensively used in classification in other areas, its effect is little studied and understood in this area. In addition to presenting a new risk classification model for LBDs this paper also adopts a rigorous approach to data sampling, calibration and testing that are absent in many existing studies. The results indicate that the neuro-fuzzy approach is a viable method for LBD risk classification.