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This study introduces a fast, 2-minute method to personalize exoskeleton assistance by mimicking human joint moments. This approach enhances exoskeleton performance, reduces user effort, and increases accessibility for everyday use.

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Area of Science:

  • Biomechanics
  • Robotics
  • Human-Computer Interaction

Background:

  • Personalized assistance enhances exoskeleton performance during locomotion.
  • Current optimization methods are inefficient, uncomfortable, and complex.

Purpose of the Study:

  • To develop a rapid, efficient, and accessible method for personalizing exoskeleton assistance.
  • To improve exoskeleton comfort, deployability, and reduce computational complexity.

Main Methods:

  • A novel method was developed to optimize exoskeleton assistance by imitating human joint moments within 2 minutes.
  • The approach ensures stability while providing gentle, personalized torque.
  • Tested on a unilateral ankle exoskeleton with off-board actuation.

Main Results:

  • Assistance optimization was 16 times faster than state-of-the-art methods.
  • Reduced muscle activity by 36.8% and metabolic cost by 20.4%.
  • Demonstrated effective deployment across various conditions, devices, and environments.

Conclusions:

  • The method significantly reduces costs associated with exoskeleton research and operation.
  • It enhances the accessibility of effective, personalized, and continuously tuned exoskeletons for daily scenarios.
  • The approach overcomes limitations of existing methods regarding feedback, tuning, and assistance formulation.