Fuzzy Logic Mechanism for an improved Assessment into Lifting related injury risks among Nigeria women.

In this study a fuzzy logic model was adopted to assess the severity of risk involved in lowering and/or lifting by Nigeria women using three risk factors of weight (Kg), height of load (cm) and the handlers’ arm reach (cm). The leading objective is to provide an improved assessment tool to Risk Assessment Filter (RAF). The algorithm of the fuzzy inference engine applied sets of 64 linguistic rules to generate the output variable in Lifting/lowering risk. The Spearman’s rank correlation value of 0.85 at the confidence level of 0.01, indicated no significant difference between the initial assessors suspections of risk with the use of RAF and the developed model prediction. The risk values and interpretations generated by the model were confirmed not just similar to, but with better information than, using RAF. The study proposed a model for an improved injury risk assessment than RAF in assessment of lifting risk among women handlers. It is simple, save time and can find its usefulness in household chores and in any workplaces were women are engaged in manual lifting operations.