A Neural Networks Approach to Determine Factors Associated With Self-Reported Discomfort in Picking Tasks.

Objective: A neural networks approach has been proposed to handle various inputs such as postural, anthropometric and environmental variables in order to estimate self-reported discomfort in picking tasks. An input reduction method has been proposed, reducing the input variables to the minimum data required to estimate self-reported discomfort with similar accuracy as the neural network fed with all variables.

Background: Previous works have attempted to explore the relationship between several factors and self-reported discomfort using observational methods.