Clinical Validation of Myoelectric Implant for Intuitive Prosthesis Control

NIH RePORTER · NIH · U44 · $728,183 · view on reporter.nih.gov ↗

Abstract

Abstract The goal of this translational NIH SBIR program is to evaluate a small, implantable system for recording myoelectric signals from residual muscles of individuals with forearm amputations. The signals will be wirelessly coupled to an external transceiver for controlling a prosthesis. Compared to conventional surface electrodes, this system will provide: • more channels for prosthesis control from a larger number of muscles in the residual limb, • improved specificity and repeatability for recording from individual muscles and muscle groups, • higher reliability and quality for the recorded signals under different socket conditions, • selective, consistent signals from deep muscles, and • the ability to use gel, vacuum, and other prosthesis socket lining systems that do not easily accommodate surface electrodes. These multichannel recordings will enable users to generate simultaneous multi-axis movements with a more natural feel of control than existing myocontrollers that only actuate a single joint axis at a time. In Phase I, we will complete upgrades and testing of the external transceiver to eliminate the need of the belt-worn processor. In Phase II, we will conduct an early feasibility IDE study in conjunction with the University of Pittsburgh. We will coordinate nationwide recruitment along with Advanced Arm Dynamics to enroll a sufficient number of subjects to implant 5 subjects with the myoelectric implant for a 1-year study. Subjects will be implanted and undergo quarterly evaluation at the University of Pittsburgh throughout the 1-year take-home study. The implant will be evaluated for safety and efficacy for controlling a multi-articulating prosthetic limb.

Key facts

NIH application ID
10290697
Project number
1U44NS123301-01
Recipient
RIPPLE, LLC
Principal Investigator
Scott Hiatt
Activity code
U44
Funding institute
NIH
Fiscal year
2022
Award amount
$728,183
Award type
1
Project period
2022-06-01 → 2023-05-31