Individualized exoskeleton design for construction workers based on biomechanical digital twins

The construction task requires high physical strength of construction workers and is easy to lead to physical fatigue of construction workers. Many construction tasks typically result in accidents and work musculoskeletal disorders (WMSD). The heavy workload will affect the safety and health of workers and will also exacerbate the labor shortage in the construction industry in many countries and regions, including Hong Kong. The exoskeleton, as a wearable external mechanical structure, may benefit workers by reducing their physical workload and improving their productivity. My research focuses on developing a biomechanical digital twin to assist the individualized design of exoskeletons for construction workers.

This research would apply a non-intrusive method to collect the kinematic data and establish a musculoskeletal model for construction workers. The method combines computer vision technology which is a 3D motion capture algorithm using an RGB camera and smart insoles for construction workers which is capable of monitoring the reaction force of feet generated by a work pattern. The potential, feasibility, and applicability of industrial exoskeletons applied to construction workers will be analyzed. Based on the musculoskeletal model, the biomechanical analysis will be carried out to identify exceptionally loaded positions, analyze representative muscle groups and joint loads of each pose representative of the model, find over-strained body areas and add exoskeletons. Then propose a model-based framework will be proposed to optimize and evaluate the individual exoskeleton design for construction workers. And, using the model-based approach to extend worker actions from poses to movement sequences. The research will accelerate the application of exoskeleton for construction workers.