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Viability, task switching, and fall avoidance of the simplest dynamic walker.

Navendu S Patil1,2, Jonathan B Dingwell3, Joseph P Cusumano4

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Task-level motor regulation, like maintaining walking speed, is crucial for fall avoidance in humans. An adaptive hierarchical control strategy using task switching may offer a low-information-cost method for preventing falls.

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Area of Science:

  • Biomechanics
  • Robotics
  • Neuroscience

Background:

  • Human walking exhibits versatile control for task achievement (e.g., obstacle avoidance).
  • The role of this versatile control in fall avoidance was previously unknown.
  • A functional link between task-goal motor regulation and disturbance rejection in walkers was recently established.

Purpose of the Study:

  • To investigate the relevance of versatile walking control to fall avoidance.
  • To identify the viability kernel for a speed-regulated walking model.
  • To explore the potential of adaptive hierarchical control for fall prevention.

Main Methods:

  • Analysis of a simplified walking model to determine the viability kernel.
  • Identification of state-space regions allowing perpetual walking through push-off inputs.
  • Evaluation of how basins of attraction for steady-state gaits cover the viability kernel.

Main Results:

  • The viability kernel was identified as the largest state-space region for sustained walking.
  • A limited number of speed-regulated gait basins of attraction were found to cover the viability kernel.
  • This suggests task-level motor regulation plays a significant role in fall avoidance.

Conclusions:

  • An adaptive hierarchical control strategy, switching between task-level regulators, is proposed for fall avoidance.
  • This controller requires only a target value for the regulated observable at each step.
  • The low "information cost" for biological implementation, including human cognitive demands, is highlighted.