2014 Annual Meeting Abstracts
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Neuroprosthetic Hand Real-Time Proportional Control by Rodent Regenerative Peripheral Nerve Interfaces
Christopher M. Frost, BME, Daniel C. Ursu, MS, Andrej Nedic, MBE, Cheryl A. Hassett, BS, Jana D. Moon, BS, Shoshana L. Woo, MD, R Brent Gillespie, PhD, Paul S. Cederna, MD, Nicholas B. Langhals, P, Melanie G. Urbanchek, PhD.
University of Michigan, Ann Arbor, MI, USA.

PURPOSE:
Regenerative peripheral nerve interfaces (RPNIs) are implantable bioartifical interfaces for signal transduction between peripheral nerves and prosthetic limbs. RPNIs implanted into rats have shown long-term stability and viability for up to 2 years. To date, control algorithms for translating RPNI signals into real-time control of a neuroprosthetic limb have not been demonstrated. The purposes of this study were to: a) design and validate a system for translating RPNI signals into real-time control of a neuroprosthetic hand; and b) use the RPNI system to demonstrate proportional control of a neuroprosthetic hand.
METHODS:
Three groups were created in a rat model: Control (n=2), Denervated (n=1), and RPNI (n=3). For the Control group, the soleus muscle was denervated and a proximal and distal tenotomy with repair was performed. For RPNI and denervated groups, a free soleus muscle was transferred to the lateral compartment of the ipsilateral thigh. In the RPNI group the transferred muscle was reinnervated with the divided tibial nerve. In all groups, bipolar stainless steel wire electrodes were positioned on the muscle. Evaluation was performed 4-5 months after implantation. Voluntary movements were evoked in response to Von Frey monofilament stimulation on the lateral ankle. Using a peak detection algorithm in LabView, muscle RPNI activity was scanned in 300-msec windows and integrated in real-time. Rat movements were videographed in high speed (120 fps). In total, 1040 control and 876 RPNI prosthesis activations were analyzed. The RPNI Processing System was validated against Control and Denervated group signal recording and activation of neuroprosthetic
RESULTS:
Voluntary rat movement activated the prosthesis in Control and RPNI groups reliably throughout the testing period of up to 15 continuous minutes with no observable instrumentation failure or biological fatigue. As expected, leg movement in the denervated group did not activate the prosthesis further validating the RPNI system and indicating minimal signal contamination from surrounding muscle groups. Signal to noise ratio between resting iRPNI and iRPNI after leg movement was excellent across control and RPNI groups (3.55 and 3.81, respectively). “Sensitivity” to accurately detect activation after stimulation and “specificity” to prevent unwanted activation during rest were also accurate across RPNI, control, and denervated groups (each ratio≥0.9). Both RPNI and control groups showed a logarithmic increase in iRPNI with increasing Von Frey filament size (R2 = 0.758 and R2 = 0.802, respectively). Higher iRPNI increased output voltage to the prosthesis giving graded, proportional control to hand speed.
CONCLUSION:
This study demonstrates for the first time that an RPNI can be used to directly control a prosthetic arm. Signal contamination from muscles adjacent to the RPNI is minimal. Further, the RPNI can provide reliable proportional control of prosthesis hand speed. Sponsor: Defense Advanced Research Projects Agency Contract No. N66001-11-C-4190.


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