Prosthetic fitting is often a painful and lengthy process.

In some cases, determining the patient's ability to operate the prosthesis before it is fitted can be a problem.

Researchers in North Carolina and Arizona have demonstrated a new technology designed to make it easier for patients and clinicians to assemble prosthetic limbs.

 

 

Using virtual reality and reinforcement learning, researchers in North Carolina and Arizona are demonstrating an entirely new technology designed to help patients and clinicians more easily assemble prosthetic limbs:

Surgeons of OrthoCarolina in Charlotte, N.C., are using VR to prove that patients born with deformed hands can control their prosthetic hands without having to undergo targeted muscle-nerve reassignment surgery.

At the University of North Carolina, the University of North Carolina at Chapel Hill and Arizona State University, engineering professors are demonstrating an adjustment algorithm based on reinforcement learning that allows patients to reduce the assembly time of robotic knees from hours to about 10 minutes.

 

Participants in the study were tested in a digital virtual reality unit in the COAPT Complete Control Room, while the researchers wanted to measure the performance of the prosthetics they regularly developed.

As the patient focuses on moving the limb, the system tracks multiple degrees of freedom, or the patient's ability to move the arm at different points in space.

Sensors placed along the forearm detect muscle activity and are designed to determine whether each limb can accurately reproduce the movement of the prosthetic limb.

 

"Without VIRTUAL reality, I don't think we can objectively measure performance of one with prosthetic limbs," Gart says.

In theory this could be done, but it may be a subjective interpretation.

With VR, you can pinpoint exactly where you want your virtual limbs to be in space and only count them as complete if they match exactly.

That definitely increases its research value."

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