A Sensor-Based Approach for Automatic and Objective Ergonomic Risk Indices Calculation

It is crucial to prioritize the prevention of work-related musculoskeletal disorders within manufacturing contexts. However, traditional approaches to ergonomic risk assessment often lack efficiency, and objectivity, and are time-consuming. This study focuses on the use of wearable sensors to improve ergonomic risk evaluation. By leveraging this approach, the automatic calculation of ergonomic risk indices across various standard methodologies becomes feasible. The process integrates data from Xsens, Manus gloves, an electromyography system, and traditional measuring tools ensuring comprehensive evaluation. The procedures for calculating ergonomic risk indices according to several standard methods (e.g., RULA, OCRA, and NIOSH) are presented. Continuous monitoring of worker activities and streamlined analysis processes result in notable enhancements in accuracy, reduction of assessment time, and mitigation of potential biases associated with manual observation. Industrial experiments conducted to validate the effectiveness of the proposed method underscore its ability to objectively evaluate physical ergonomic risks. Future research could focus on refining algorithms to improve data processing efficiency.