Traumatic peripheral nerve injuries suffered during amputation commonly results in debilitating neuropathic pain in the affected limb. Modern prosthetic technologies allow for intuitive, simultaneous control of multiple degrees of freedom. However, these state-of-the-art devices require separate, independent control signals for each degree of freedom, which is currently not possible. As a result, amputees reject up to 75% of myoelectric devices preferring instead to use body-powered artificial limbs which offer subtle sensory feedback. Without meaningful and intuitive sensory feedback, even the most advanced myoelectric prostheses remain insensate, burdensome, and are associated with enormous cognitive demand and mental fatigue. The ideal prosthetic device is one which is capable of providing intuitive somatosensory feedback essential for interaction with the environment. Critical to the design of such a bioprosthetic device is the development of a reliable biologic interface between human and machine. This ideal patient-prosthetic interface allows for transmission of both afferent somatosensory information and efferent motor signals for a closed-loop feedback system of neural control. Our lab has developed the Regenerative Peripheral Nerve Interface (RPNI) as a biologic nerve interface designed for stable integration of a prosthetic device with transected peripheral nerves in a residual limb. The RPNI is constructed by surgically implanting the distal end of a transected peripheral nerve into an autogenous muscle graft. Animal experiments in our lab have shown recording of motor signals from RPNI’s implanted into both rodents and monkeys. Here, we achieve high amplitude EMG signals with a high signal to noise (SNR) ratio.
Stephen W. P. Kemp, Melanie G. Urbanchek, Zachary T. Irwin, Cynthia A. Chestek, and Paul S. Cederna, "Development of regenerative peripheral nerve interfaces for motor control of neuroprosthetic devices," Proc. SPIE 10194, Micro- and Nanotechnology Sensors, Systems, and Applications IX, 1019415 (Presented at SPIE Defense + Security: April 10, 2017; Published: 18 May 2017); https://doi.org/10.1117/12.2264130.
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