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New Tech May Make Prosthetic Hands Easier for Patients to ­se


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A prosthetic hand (left) and a natural hand.

Researchers at North Carolina State University and State University of North Carolina at Chapel Hill have developed a way to translate neuromuscular signals into movements for prosthetic wrists and hands.

Credit: NC State News

North Carolina State University (NCSU) and University of North Carolina at Chapel Hill researchers have developed technology for translating neuromuscular signals into movements for prosthetic wrists and hands, using computer models that emulate natural elements in the appendages.

NCSU's Helen Huang says their solution bypasses the tedious process of relying on pattern recognition via machine learning in favor of a user-generic, musculoskeletal model.

The team first tracked volunteers as they performed wrist and hand actions to record their neuromuscular signals, which were fed to the generic model. The model then interpreted those signals as commands to the powered prosthetic.

"By incorporating our knowledge of the biological processes behind generating movement, we were able to produce a novel neural interface for prosthetics that is generic to multiple users, including an amputee in this study, and is reliable across different arm postures," Huang says.

From NC State News
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