Available Technologies

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Featured Technologies

Powered Prosthesis Controller With Adaptive Control For Climbing Stairs

ID U-7065

Category Medical Devices

Subcategory Prosthetics

Researchers
Brief Summary

Adaptive controller for above-knee prosthesis users who interact with differently sized steps in the real world.

Problem Statement

During walking, conventional prosthesis-wearing individuals with an above-knee amputation perform compensatory movements with their sound side, residual limb, and upper body to make up for their passive prosthesis deficiencies. These movements lead to musculoskeletal issues and embarrassing moments for users if a fall occurs. Currently, powered prostheses using controllers with fixed trajectories cannot adapt to different step heights and gait patterns. If a user attempts to climb a taller step than the one the stair controller was tuned for, the prosthesis may not provide enough clearance and cause a fall. Even if the user clears the step, through compensatory movements, the prosthetic foot may not lay flat on the step. When the prosthetic knee starts generating torque, as necessary to climb the step, the subject may be pushed backward and potentially fall down the stairs. Most powered knees only handle one size of step.

Technology Description

University of Utah researchers have created an adaptive controller that makes constant and continuous calculations to ensure the right action is being taken dependent on the size of step. This constant calculation allows the user to do perform actions they couldn't with other prostheses.

Stage of Development

Pre-Clinical Validation

Benefit

  • Allows users to take two steps at a time.
  • Enables shuffle stepping.
  • Waits for user to move before engaging the stepping process.
  • Offers stepping ability with ADA compliant 4"-7" steps.

Publications

Hood, Sarah; Gabert, Lukas; Lenzi, Tommaso (2020): Powered Knee and Ankle Prosthesis with Adaptive Control Enables Climbing Stairs with Different Stair Heights, Cadences, and Gait Patterns. TechRxiv. Preprint. https://doi.org/10.36227/techrxiv.13177109.v1 

Contact Info

Huy Tran
(801) 581-7792
huy.tran@utah.edu

Questions?

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