Surrogate representation of a task as a method for data reduction in calculating cumulative spinal loading

Abstract

The goal of the current investigation was to propose and evaluate a method for estimating cumulative spinal loading based on the hypothesis that cumulative loading for a single task will be linearly proportional to its cycle time. The association between cumulative spinal loading and low-back pain has driven ergonomists and researchers to develop new methods for estimating cumulative workplace exposure. Despite new advances that reduce the amount of data for analysis, methods are still quite labour intensive and prohibitive for widespread industrial usage. In order to assess the proposed method, 15 workers performing six tasks from four different job cells were analysed by video analysis. Two equations to predict cumulative loading of a task based on the known cumulative loading of a similar task were developed. An ‘interpolation’ equation used a task with a longer cycle time to predict cumulative spinal loading for a similar task with a shorter cycle time. An ‘extrapolation’ equation allowed for the opposite prediction to occur. These estimates were compared to a criterion measure produced from the video analysis. There were no significant differences between the criterion measure and the estimated output from the proposed prediction method for four of the five cumulative loading variables. Cumulative compression was the most accurately predicted variable (3.9%). A large range of relative per cent errors (23–202.4%) were found for cumulative shear and extension moment. The proposed method produced promising results for estimating cumulative loading in tasks that differ in length but have similar musculoskeletal demands, especially when combined with other methods of data reduction and has the potential to be used to proactively estimate cumulative loading and quickly screen for tasks that are in need of a full, in depth analysis. Further investigation into defining criteria for ‘similar’ tasks, the influence of task constituent components, and its use in other areas of industry is necessary before the approach should be widely employed.