Abstract

Biomechanically-assisted models have been developed to estimate spine tissue loads in vivo and used to assess the potential risk of injuries in workers. However, most biomechanical models represented trunk muscles as straight-lines vectors acting between a muscle origin and insertion. Even though straight-line muscles behaved reasonably well in simple dynamic occupational tasks, this assumption could be problematic in complex multidimensional dynamic tasks that include highly asymmetric or extreme bending postures. Previous efforts at developing curved muscle models were not empirically validated or tested under dynamic loading conditions. Hence, the accuracy of spine tissue load estimations of such models has not been well documented. In this study, a curved muscle representation was developed and validated to overcome this concern. The objective of this study was to investigate the model fidelity of a biologically-assisted curved muscle model during complex dynamic lifting tasks. Twelve subjects (7 males and 5 females) participated in this study. Subjects performed dynamic lifting tasks as a function of load weight, load origin, and load height to simulate complex lifting activities from extreme and highly dynamic postures. The moment matching measures were calculated to evaluate how well model estimated the spinal moment of L5/S1 compared to measured spinal moments in terms of correlation (R2) and average absolute error (AAE). The model demonstrated good repeatability and very good model fidelity between various experimental conditions. The mean and standard deviations of multi-planar R2 were 0.85 (0.07), with 78% of all trials (411/528) having R2 > 0.8. For the multi-planar normalized AAE (%), mean and standard deviations were 12.1% (3.9), with 80% of all trials (425/528) having AAE < 15%. The results of this study indicated that curved muscle representation in the biologically-assisted model was an empirically reasonable approach to estimate accurate spine tissue loads of the lumbar spine during complex occupational circumstances.

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