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A Unified Controller for Natural Ambulation on Stairs and Level Ground with a Powered Robotic Knee Prosthesis



Details

  • Personal Author:
  • Description:
    Powered lower-limb prostheses have the potential to improve amputee mobility by closely imitating the biomechanical function of the missing biological leg. To accomplish this goal, powered prostheses need controllers that can seamlessly adapt to the ambulation activity intended by the user. Most powered prosthesis control architectures address this issue by switching between specific controllers for each activity. This approach requires online classification of the intended ambulation activity. Unfortunately, any misclassification can cause the prosthesis to perform a different movement than the user expects, increasing the likelihood of falls and injuries. Therefore, classification approaches require near-perfect accuracy to be used safely in real life. In this paper, we propose a unified controller for powered knee prostheses which allows for walking, stair ascent, and stair descent without the need for explicit activity classification. Experiments with one individual with an above-knee amputation show that the proposed controller enables seamless transitions between activities. Moreover, transition between activities is possible while leading with either the sound-side or the prosthesis. A controller with these characteristics has the potential to improve amputee mobility. [Description provided by NIOSH]
  • Subjects:
  • Keywords:
  • ISBN:
    9781665491907
  • ISSN:
    2153-0866
  • Publisher:
    Institute of Electrical and Electronics Engineers (IEEE)
  • Document Type:
    Text
  • Funding:
    Grant
  • Genre:
    Proceedings
  • Place as Subject:
  • CIO:
    National Institute for Occupational Safety and Health (NIOSH)
  • Topic:
    Workplace Safety & Health
  • Location:
    North America
  • NIOSHTIC Number:
    nn:20069148
  • Citation:
    Proceedings of the 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023, October 1-5, 2023, Detroit, Michigan. New York: Institute of Electrical and Electronics Engineers (IEEE), 2023 Oct; :2146-2151
  • Email:
    marissa.cowan@utah.edu
  • Federal Fiscal Year:
    2024
  • Performing Organization:
    University of Utah
  • Peer Reviewed:
    False
  • Start Date:
    20050701
  • Source Full Name:
    Proceedings of the 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2023, October 1-5, 2023, Detroit, Michigan
  • End Date:
    20280630
  • Collection(s):
  • Main Document Checksum:
    urn:sha-512:798a9e2081b1dffdcfe2f5506f07aead7190b1e26f037db98a7f00067589799cae6f2e43473baec8ae3c5e2d9274b6400c67542fa2758f96953a7e750c5b5bab
  • Download URL:
  • File Type:
    Filetype[PDF - 633.07 KB ]
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