A Flexible Robotics-Inspired Computational Model of Compressive Loading on the Human Spine

Abstract

The use of powerful robotics tools in modeling and analysis of complex biomechanical systems has led to the development of computationally effective and scalable human models. Our early work in this regard focused on a humanoidsbased rigid-body modeling of human kinodynamics to monitor instantaneous and accumulating effects of external loads on body joints. Nevertheless, despite their high-computational efficiency, the flexible nature of the spine and its characteristic were not taken into account, resulting in less accurate estimations of the spinal compressive forces. Accordingly, in this work, we propose a flexible model of the human spine mechanics for assessing compressive loading, and integrate it in our robotics-based whole-body model. Such a model can quantify the compressive force distribution along the spine and the muscles' activity for a measured back configuration and known external forces, which both contribute to increasing the ergonomic risk level. The muscles' activity predictions are validated through an experimental analysis on six human subjects. Three different tests are conducted considering different loading conditions. Results demonstrate the potential of the proposed approach in monitoring the spine compressive loading and predicting a muscles activity with an average accuracy of 10% against experimental data. Minimizing the required number of sensors and the amount of computational resources, the presented approach is particularly suitable for online risk evaluation in a real working scenario.

Ergonomic human-robot collaboration in industry: A review

“…In the same line, Gholami et al (2022) introduced a set of quantitative metrics to take into account operators’ ergonomics in the assessment of teleoperation interfaces. Still chasing a reduced-complexity approach but adding a certain level of accuracy for more sophisticated body districts, Ventura et al (2021) developed a flexible model of the human spine mechanics for assessing compressive loading. Finally, Latella et al (2019) presented a stochastic methodology for the simultaneous floating-base estimation of the human whole-body kinematics and dynamics toward online ergonomics assessment.…”

Towards the adoption of wearable exoskeletons in occupational workspaces: model-based assessment and control of back-support exoskeletons

“…Previous studies have proposed tools for real-time lumbar compression forces estimation. However, these were static optimization-based approaches [139,140] or lacked a detailed representation of musculoskeletal geometries or EMG-to-activation physiological processes [78][79][80], thus, hampering estimation accuracy and ultimately, their applicability to real-world scenarios.…”