Development of Biomechanical Force Prediction Model Using Motion Data

Faculty Researcher: SangHyun Lee, PhD, Assistant Professor of Civil & Environmental Engineering at the University of Michigan

Injuries and fatalities due to falls from ladders are common in construction. Considering the fact that most falls from ladders are caused by unsafe behaviors exhibited during ladder climbing (HSPH 2010), identifying and correcting these behaviors is very important for reducing the risk of falls from ladders. From this perspective, PIs Lee and Woolley and Prof. Armstrong (Advisor for this proposal) are developing a computer vision-based field tool to monitor and evaluate worker posture and movement patterns during ladder-climbing activities. This tooldevelopment is funded by CPWR (Center for Construction Research and Training). However, this tool has a great potential to be extended to a comprehensive biomechanical analysis field tool with the addition of a scientific mechanism to estimate hand and foot forces, which is lacking in the CPWR project. Further, adding an effective means to provide a worker with feedback on his/her climbing style could significantly reduce injuries. To address these issues, this research aims to develop a biomechanical force prediction model that utilizes motion data, which does not require direct force measurement. Several researchers (Hakkinen et al. 1988; Bloswick and Chaffin 1990; Armstrong et al. 2008) proved that the forces on hands and feet are closely related to workers’ motions. Thus, we will conduct a series of lab experiments to collect motion and force data using the motion capture and force measurement devices at the UM 3D Lab and Ergonomics Lab. This data will be used to identify quantitative relationships between forces and motions. In addition, workers’ postures that are captured by the field tool will be animated in a virtual environment using Blender, an open-source 3D graphics program, to overcome the challenge of having ineffective means of providing a worker with feedback on his/her climbing style. Such animation will greatly contribute to a worker’s understanding of the differences between his/her own postures and the recommended ones, such that he/she can effectively learn a climbing style that minimizes loads on his/her body.