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Low back pain is prevalent among industrial workers due to heavy lifting and poor posture, causing significant back injuries globally and affecting health and productivity. Existing back-support exoskeletons (BSEs) lack closed-loop control for musculotendon unit (MTU) or joint loads. This study proposes a framework for closed-loop control of L5/S1 joint loads, featuring a simplified BSE dynamics model, a muscle excitation predictor (MEP), and a nonlinear model predictive control (NMPC) algorithm. The simplified model matches the neuromusculoskeletal model with a correlation %0.98, and the MEP has a prediction accuracy of 0.86 ± 0.06. Future work will develop the MPC algorithm to finalize the control framework.

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Towards Predictive Control of Trunk Internal Loads: Modeling Musculotendon Loads and Predicting Muscle Excitations

  • 会议论文

  • 发表日期：

    2025年

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  • Youhan Li,
  • Massimo Sartori,
  • Mahdi Nabipour

摘要

Low back pain is prevalent among industrial workers due to heavy lifting and poor posture, causing significant back injuries globally and affecting health and productivity. Existing back-support exoskeletons (BSEs) lack closed-loop control for musculotendon unit (MTU) or joint loads. This study proposes a framework for closed-loop control of L5/S1 joint loads, featuring a simplified BSE dynamics model, a muscle excitation predictor (MEP), and a nonlinear model predictive control (NMPC) algorithm. The simplified model matches the neuromusculoskeletal model with a correlation %0.98, and the MEP has a prediction accuracy of 0.86 ± 0.06. Future work will develop the MPC algorithm to finalize the control framework.