Self-Aligning Mechanism Improves Comfort and Performance with a Powered Knee Exoskeleton

Details

• Personal Author:
  Ishmael MK ; Lenzi T ; Sarkisian SV
• Description:
  Misalignments between powered exoskeleton joints and the user's anatomical joints are inevitable due to difficulty locating the anatomical joint axis, non-constant location of the anatomical joint axis, and soft-tissue deformations. Self-aligning mechanisms have been proposed to prevent spurious forces and torques on the user's limb due to misalignments. Several exoskeletons have been developed with self-aligning mechanisms based on theoretical models. However, there is no experimental evidence demonstrating the efficacy of self-aligning mechanisms in lower-limb exoskeletons. Here we show that a lightweight and compact self-aligning mechanism improves the user's comfort and performance while using a powered knee exoskeleton. Experiments were conducted with 14 able-bodied subjects with the self-aligning mechanism locked and unlocked. Our results demonstrate up to 15.3% increased comfort and 38% improved performance when the self-aligning mechanism was unlocked. Not surprisingly, the spurious forces and torques were reduced by up to 97% when the self-aligning mechanism was unlocked. This study demonstrates the efficacy of self-aligning mechanisms in improving comfort and performance for sit-to-stand and position tracking tasks with a powered knee exoskeleton. [Description provided by NIOSH]
• Subjects:
  Anatomy Biomechanical Phenomena Occupational Health Safety
• Keywords:
  Author Keywords: Exoskeleton Comfort Biomechanical Engineering Biomechanics Equipment Design Exoskeletons Human-robot Misalignment Lower Extremities Prosthetic Devices Rehabilitation Robotics Robotics Wearable Robotics

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• ISSN:
  1534-4320
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  OSHA Region 8 ; Utah
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Volume:
  29
• NIOSHTIC Number:
  nn:20068134
• Citation:
  IEEE Trans Neural Syst Rehabil Eng 2021 Mar; 29:629-640
• Contact Point Address:
  Sergei V. Sarkisian, Department of Mechanical Engineering, Utah Robotics Center, The University of Utah, Salt Lake City 84112 USA
• Email:
  sergei.sarkisian@utah.edu
• Federal Fiscal Year:
  2021
• Performing Organization:
  University of Utah
• Peer Reviewed:
  True
• Start Date:
  20050701
• Source Full Name:
  IEEE Transactions on Neural Systems and Rehabilitation Engineering
• End Date:
  20280630
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:c854f24aa594a28395e3029613ff14539fe22fa0f19dab5f0abbbf1765fee92b8734e01db92a6658eb3511c4cb7955fbf6efe5353b9077074d998edfc1c94438
• Download URL:
  https://stacks.cdc.gov/view/cdc/230349/cdc_230349_DS1.pdf
• File Type:
  [PDF - 2.57 MB ]