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The interplay of fatigue dynamics and task achievement using optimal control predictive simulation.

P Puchaud1, B Michaud1, M Begon1

  • 1Laboratoire de Simulation et Modélisation du Mouvement, Département de Kinésiologie, Université de Montréal, Laval, Canada.

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Summary

Predictive models of human motion can now simulate fatigue. By integrating a muscle fatigue model with rigid-body dynamics, researchers revealed distinct anticipatory and reactive strategies for optimizing repetitive tasks and reducing injury risk.

Keywords:
Biceps curlsBiomechanicsDirect multiple shootingKinematic variabilityNMPCPredictive simulation

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Area of Science:

  • Biomechanics
  • Human Motion Simulation
  • Fatigue Modeling

Background:

  • Predictive human motion simulation is crucial for optimizing techniques in repetitive tasks.
  • Current models often minimize actuator activations, inaccurately assuming this minimizes fatigue.
  • A deeper understanding of fatigue-induced adaptations is needed for realistic motion prediction.

Purpose of the Study:

  • To develop an advanced model for simulating fatigue-induced adaptations in human motion.
  • To investigate muscle fatigue's impact on movement strategies during repetitive tasks.
  • To compare different optimal control problem (OCP) formulations for fatigue simulation.

Main Methods:

  • Interfaced Xia's three-compartment fatigue model with rigid-body dynamics.
  • Incorporated a stabilization invariant into Xia's fatigue model for direct multiple shooting.
  • Simulated maximum repetitions of dumbbell biceps curls using OCPs with varying cost functions and horizons.

Main Results:

  • Sliding-horizon OCPs (20-21 reps) showed kinematic deviations to a swinging strategy as fatigue increased.
  • Full-horizon OCPs (32 reps) utilized the swinging strategy throughout, predicting more repetitions.
  • Sliding-horizon OCPs demonstrated reactive strategies for torque minimization and anticipatory strategies for fatigue minimization.

Conclusions:

  • The integrated model accurately predicts fatigue-induced kinematic adaptations.
  • Different OCP formulations reveal distinct anticipatory and reactive fatigue management strategies.
  • This approach offers potential for performance optimization and reducing fatigue-related injuries.