Ergonomic risk reduction in picking activities: evaluation of an active exoskeleton through Azure Kinect

Abstract

Reducing the ergonomic risk involved in picking activities is fundamental to ensure the health of the workers by minimizing the occurrence of musculoskeletal disorders. Recently exoskeletons have been introduced to support workers and reduce the overload. In this paper exploiting a depth camera we evaluated the risk involved in picking activities with and without the support of an active exoskeleton. For the scope 5 different subjects performed 42 lifting actions with and without the active exoskeleton for a total of 420 total lifts. The task was to reproduce a real logistical scenario of palletizing boxes in the laboratory. The lifting actions were recorded in a laboratory setting with the Azure Kinect depth camera benchmarking the posture with and without the active exoskeleton. For the risk assessment we exploited a tool based on the Azure Kinect to automatically calculate the NIOSH lifting equation named AzKNIOSH. Results statistically demonstrated that the exoskeleton does not affect the posture during the lift while it has a beneficial effect on the lifting index considering a decreased load weight.

Keywords: Ergonomic, Machine Vision, Exoskeleton

DOI: 10.54941/ahfe1005184