Motion Data-Driven Biomechanical Analysis during Construction Tasks on Sites

Abstract

Work-related musculoskeletal disorders (WMSDs) are one of the major health issues that workers frequently experience due to awkward postures or forceful exertions during construction tasks. Among available job analysis methods, biomechanical models have been widely applied to assess musculoskeletal risks that may contribute to the development of WMSDs based on motion data during occupational tasks. Recently, with the advent of vision-based motion capture approaches, it has become possible to collect the motion data required for biomechanical analysis under real conditions. However, vision-based motion capture approaches have not been applied to biomechanical analysis because of compatibility issues in body models of the motion data and computerized biomechanical analysis tools. To address this issue, automated data processing is focused on to convert motion data into available data in existing biomechanical analysis tools, given the BVH motion data from vision-based approaches. To examine the feasibility of the proposed motion data processing, an experiment for both static and dynamic biomechanical analyses was conducted on lifting tasks. The results indicate that vision-based motion capture data-converted as proposed in this paper-can provide a sufficient level of detail on human kinematics to conduct biomechanical analysis, thus allowing for the identification of particular body parts where excessive forces are placed during tasks. The issues and directions of future research are also discussed to perform on-site biomechanical analysis during construction tasks.