Safe lifting: An adaptive training system for factory workers using the Microsoft Kinect

One of the biggest challenges facing Americans working in industrial factories is the risk of developing musculoskeletal disorders (MSDs). About 2% of all American workers suffer from MSDs every year. This has a significant social consequence on the lives of workers and places a large burden on the employers, as MSDs account for over one-third of all worker compensation costs. Still-frame models developed to reduce work-related MSDs either require expertise or lack real-time analysis. The focus of this project was to design an accurate monitoring system that could help factory workers correct their heavy-lifting technique by making adaptive technique recommendations. To observe human lifts, we made use of the Microsoft Kinect depth sensing camera, which has the ability to provide real-time skeletal tracking at 30 frames per second. Proper lifting techniques were defined using several lifting equations and various biomechanical models. Knowledge of the user's joint angles allows us to assess lift safety. In our system design, users are first asked to perform several lifts in different canonical styles. The system then provides the user with a recommended lifting style that maximizes safety within the constraints of the user's measured capabilities.