Advancing Towards Automated Ergonomic Assessment: A Panel of Perspectives

Abstract

AbstractDirect and continuous exposure measurement has posed challenges to human factors engineering (HFE) professionals when conducting risk assessments. However, emerging technologies have utility to automate elements of HFE assessment and strengthen opportunities for direct and continuous exposure measurement. Leading HFE researchers provide perspectives on how advances in technology and computing, including computer vision, machine learning and wearable sensors, can aid in the automation of exposure measurement to inform ergonomic assessment while also bolstering the opportunities for objective, data-driven insight. Drs. SangHyun Lee and Michael Sonne share perspectives on the development and validation of computer vision-based pose estimation approaches. Such pose estimation approaches allow HFE professions to record video data where software can convert video into a kinematic representation of a worker and then calculate corresponding joint angles without the need for any tedious posture matching, or additional post processing approaches. Dr. Cavuoto discusses how wearable technologies can unobtrusively measure kinematics in work, showcasing the potential of direct measurement, data-driven injury risk assessment. Finally, Dr. Gallagher showcases how data collected through automated approaches can be integrated with models to evaluate injury risk through a fatigue-failure injury mechanism pathway. In addition to showcasing how emerging technologies and approaches may enhance exposure and risk assessment in HFE, panelists also highlight anticipated challenges and barriers that need to be addressed to support more ubiquitous integration of such technologies into HFE assessment practice. The future for innovation and advancement in exposure measurement and assessment is bright.KeywordsErgonomic assessmentPhysical ergonomicsArtificial intelligenceRisk assessmentComputer visionWearable technology