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Robust Control of the Human Trunk Posture Using Functional Neuromuscular Stimulation: A Simulation Study.

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Functional neuromuscular stimulation (FNS) can restore trunk movement for spinal cord injury (SCI) patients. A novel control framework using artificial neural networks and robust controllers stabilizes trunk motion without precise biomechanical knowledge.

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Area of Science:

  • Biomedical Engineering
  • Neuroscience
  • Rehabilitation Robotics

Background:

  • Spinal cord injury (SCI) often results in paralysis, limiting trunk mobility.
  • Functional neuromuscular stimulation (FNS) can activate paralyzed muscles to restore movement.
  • Controlling FNS for trunk stabilization is challenging due to complex biomechanics and nonlinear neuromuscular dynamics.

Purpose of the Study:

  • To develop a robust control framework for stabilizing trunk movements using FNS in individuals with SCI.
  • To enable precise trunk motion tracking and postural control despite unknown or complex biomechanical and neuromuscular dynamics.

Main Methods:

  • Proposed a control framework integrating a robust control module (sliding-mode controllers) and an artificial neural network (ANN) mapping mechanism.
  • Utilized an anatomy-based updating law for the ANN to ensure muscle-generated torques converge to stabilizing values.
  • Analyzed system stability using Euler-Lagrange equations with bounded disturbances for a generalized framework.

Main Results:

  • Simulations demonstrated the framework's ability to stabilize trunk movements in anterior-posterior and medial-lateral directions.
  • The proposed method showed satisfactory performance in tracking user-defined trunk motions under perturbations.
  • The ANN-based mapping effectively guided muscle activation towards desired stabilizing torques.

Conclusions:

  • The developed control framework shows significant potential for restoring trunk function in SCI patients via FNS.
  • This approach offers a viable solution for FNS control without requiring exact knowledge of individual biomechanics.
  • The findings suggest applicability in clinical settings for improving trunk mobility and posture management.