Ergonomic risk assessment based on a Bayesian-optimised expert system

Improper application of an ergonomic analysis tool increases the likelihood of high-risk jobs not being detected, thus jeopardising worker’s health. Likewise, significant time and cost may be incurred by redesigning jobs improperly identified as high risk. Utah Intelligent Data Driven Ergonomic Assessment System (IDDEAS) is an expert system that aggregates the outputs of multiple analysis tools to create a more predictive ergonomic analysis tool. Rules in the expert system were optimised by processing health outcome data from hundreds of jobs and analysing the resulting relationship between the system’s prediction and the known health outcomes. IDDEAS appears to improve in predictive ability with addition of expert knowledge and to be more accurate at predicting the level of risk than individual ergonomic analysis tools used alone. The study also provides insight into methods of quantifying health outcomes and analysis tool outputs for use in software systems that integrate or compare ergonomic information.