Optimizing Warfighter Performance with Neurally Integrated Robotic Lower Limb Prostheses

Abstract

Majority of limb loss incidents (~75%) among US Military Service members is in the lower limb. However, restoring sensorimotor function with advanced active prostheses that communicate directly with the intact nervous system falls far behind development of robotic prostheses for individuals with upper limb loss. The objective of this project is to develop and deploy a fully implantable, self-contained, neurally integratedbidirectional lower limb neuroprosthesis that can be readily incorporated into the body schema and utilized without cumbersome external components. In this project, a total of six subjects (three with trans-tibial and three with trans-femoral limb loss) will be enrolled. Electrical stimulation through nerve cuff electrodes directly excites the sensory nerves remaining in the residual limb while electromyography (EMG) signals from intramuscular electrodes are interpreted to intuitively control the actions of advanced robotic lower limb prosthesis. We examine the impact of integrating sensory feedback with EMG-controlled robotic prostheses on balance, gait, and performance during complex mobility tasks in laboratory and during use at home and in community.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2021
Accession Number
AD1161275

Entities

People

  • Ronald J Triolo

Organizations

  • Case Western Reserve University

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Amputees
  • Biomedical Engineering
  • Biomedical Research
  • Computer Programming
  • Engineering
  • Engineers
  • Lower Limb Amputations
  • Lower Limb Amputees
  • Lower Limb Prostheses
  • Medical Personnel
  • Nervous System
  • Peripheral Nervous System
  • Prostheses And Implants
  • Prosthetics
  • Residual Limbs
  • Students
  • Surgical Amputations
  • Wireless Communications

Readers

  • Neuroscience
  • Rehabilitation and Prosthetic Care for Military Service Members and Veterans with Limb Loss or Disability.

Technology Areas

  • AI & ML
  • Autonomy