Dermal Sensory Regenerative Peripheral Nerve Interface for Reestablishing Sensory Nerve Feedback in Peripheral Afferents in the Rat.

BACKGROUND: Without meaningful, intuitive sensory feedback, even the most advanced myoelectric devices require significant cognitive demand to control. The dermal sensory regenerative peripheral nerve interface (DS-RPNI) is a biological interface designed to establish high-fidelity sensory feedback from prosthetic limbs. METHODS: DS-RPNIs were constructed in rats by securing fascicles of residual sensory peripheral nerves into autologous dermal grafts, with the objectives of confirming regeneration of sensory afferents within DS-RPNIs and establishing the reliability of afferent neural response generation with either mechanical or electrical stimulation. RESULTS: Two months after implantation, DS-RPNIs were healthy and displayed well-vascularized dermis with organized axonal collaterals throughout and no evidence of neuroma. Electrophysiologic signals were recorded proximal from DS-RPNI's sural nerve in response to both mechanical and electrical stimuli and compared with (1) full-thickness skin, (2) deepithelialized skin, and (3) transected sural nerves without DS-RPNI. Mechanical indentation of DS-RPNIs evoked compound sensory nerve action potentials (CSNAPs) that were like those evoked during indentation of full-thickness skin. CSNAP firing rates and waveform amplitudes increased in a graded fashion with increased mechanical indentation. Electrical stimuli delivered to DS-RPNIs reliably elicited CSNAPs at low current thresholds, and CSNAPs gradually increased in amplitude with increasing stimulation current. CONCLUSIONS: These findings suggest that afferent nerve fibers successfully reinnervate DS-RPNIs, and that graded stimuli applied to DS-RPNIs produce proximal sensory afferent responses similar to those evoked from normal skin. This confirmation of graded afferent signal transduction through DS-RPNI neural interfaces validate DS-RPNI's potential role of facilitating sensation in human-machine interfacing. CLINICAL RELEVANCE STATEMENT: The DS-RPNI is a novel biotic-abiotic neural interface that allows for transduction of sensory stimuli into neural signals. It is expected to advance the restoration of natural sensation and development of sensorimotor control in prosthetics.

Regenerative peripheral nerve interface free muscle graft mass and function.

BACKGROUND: Regenerative peripheral nerve interfaces (RPNIs) transduce neural signals to provide high-fidelity control of neuroprosthetic devices. Traditionally, rat RPNIs are constructed with ~150 mg of free skeletal muscle grafts. It is unknown whether larger free muscle grafts allow RPNIs to transduce greater signal. METHODS: RPNIs were constructed by securing skeletal muscle grafts of various masses (150, 300, 600, or 1200 mg) to the divided peroneal nerve. In the control group, the peroneal nerve was transected without repair. Endpoint assessments were conducted 3 mo postoperatively. RESULTS: Compound muscle action potentials (CMAPs), maximum tetanic isometric force, and specific muscle force were significantly higher for both the 150 and 300 mg RPNI groups compared to the 600 and 1200 mg RPNIs. Larger RPNI muscle groups contained central areas lacking regenerated muscle fibers. CONCLUSIONS: Electrical signaling and tissue viability are optimal in smaller as opposed to larger RPNI constructs in a rat model.

Regenerative peripheral nerve interfaces for real-time, proportional control of a Neuroprosthetic hand.

INTRODUCTION: Regenerative peripheral nerve interfaces (RPNIs) are biological constructs which amplify neural signals and have shown long-term stability in rat models. Real-time control of a neuroprosthesis in rat models has not yet been demonstrated. The purpose of this study was to: a) design and validate a system for translating electromyography (EMG) signals from an RPNI in a rat model into real-time control of a neuroprosthetic hand, and; b) use the system to demonstrate RPNI proportional neuroprosthesis control. METHODS: Animals were randomly assigned to three experimental groups: (1) Control; (2) Denervated, and; (3) RPNI. In the RPNI group, the extensor digitorum longus (EDL) muscle was dissected free, denervated, transferred to the lateral thigh and neurotized with the residual end of the transected common peroneal nerve. Rats received tactile stimuli to the hind-limb via monofilaments, and electrodes were used to record EMG. Signals were filtered, rectified and integrated using a moving sample window. Processed EMG signals (iEMG) from RPNIs were validated against Control and Denervated group outputs. RESULTS: Voluntary reflexive rat movements produced signaling that activated the prosthesis in both the Control and RPNI groups, but produced no activation in the Denervated group. Signal-to-Noise ratio between hind-limb movement and resting iEMG was 3.55 for Controls and 3.81 for RPNIs. Both Control and RPNI groups exhibited a logarithmic iEMG increase with increased monofilament pressure, allowing graded prosthetic hand speed control (R2 = 0.758 and R2 = 0.802, respectively). CONCLUSION: EMG signals were successfully acquired from RPNIs and translated into real-time neuroprosthetic control. Signal contamination from muscles adjacent to the RPNI was minimal. RPNI constructs provided reliable proportional prosthetic hand control.

Adjacent regenerative peripheral nerve interfaces produce phase-antagonist signals during voluntary walking in rats.

BACKGROUND: Regenerative Peripheral Nerve Interfaces (RPNIs) are neurotized muscle grafts intended to produce electromyographic signals suitable for motorized prosthesis control. Two RPNIs producing independent agonist/antagonist signals are required for each control axis; however, it is unknown whether signals from adjacent RPNIs are independent. The purpose of this work was to determine signaling characteristics from two adjacent RPNIs, the first neurotized by a foot dorsi-flexor nerve and the second neurotized by a foot plantar-flexor nerve in a rodent model. METHODS: Two Control group rats had electrodes implanted onto the soleus (tibial nerve) and extensor digitorum longus (peroneal nerve) muscles in the left hind limb. Two Dual-RPNI group rats had two separate muscles grafted to the left thigh and each implanted with electrodes: the extensor digitorum longus was neurotized with a transected fascicle from the tibial nerve, and the tibialis anterior was implanted with a transected peroneal nerve. Four months post-surgery, rats walked on a treadmill, were videographed, and electromyographic signals were recorded. Amplitude and periodicity of all signals relative to gait period were quantified. To facilitate comparisons across groups, electromyographic signals were expressed as a percent of total stepping cycle activity for each stance and swing gait phase. Independence between peroneal and tibial nerve activations were assessed by statistical comparisons between groups during stance and swing. RESULTS: Electromyographic activity for Control and Dual-RPNI rats displayed alternating activation patterns coinciding with stance and swing. Significant signal amplitude differences between the peroneal and tibial nerves were found in both the Control and Dual-RPNI groups. Non-inferiority tests performed on Dual-RPNI group signal confidence intervals showed that activation was equivalent to the Control group in all but the peroneal RPNI construct during stance. The similar electromyographic activity obtained for Control and RPNI suggests the latter constructs activate independently during both stance and swing, and contain minimal crosstalk. CONCLUSIONS: In-vivo myoelectric RPNI activity encodes neural activation patterns associated with gait. Adjacent RPNIs neurotized with agonist/antagonist nerves display activity amplitudes similar to Control during voluntary walking. The distinct and expected activation patterns indicate the RPNI may provide independent signaling in humans, suitable for motorized prosthesis control.

In vivo characterization of regenerative peripheral nerve interface function.

OBJECTIVE: Regenerative peripheral nerve interfaces (RPNIs) are neurotized free autologous muscle grafts equipped with electrodes to record myoelectric signals for prosthesis control. Viability of rat RPNI constructs have been demonstrated using evoked responses. In vivo RPNI characterization is the next critical step for assessment as a control modality for prosthetic devices. APPROACH: Two RPNIs were created in each of two rats by grafting portions of free muscle to the ends of divided peripheral nerves (peroneal in the left and tibial in the right hind limb) and placing bipolar electrodes on the graft surface. After four months, we examined in vivo electromyographic signal activity and compared these signals to muscular electromyographic signals recorded from autologous muscles in two rats serving as controls. An additional group of two rats in which the autologous muscles were denervated served to quantify cross-talk in the electrode recordings. Recordings were made while rats walked on a treadmill and a motion capture system tracked the hind limbs. Amplitude and periodicity of signals relative to gait were quantified, correlation between electromyographic and motion recording were assessed, and a decoder was trained to predict joint motion. MAIN RESULTS: Raw RPNI signals were active during walking, with amplitudes of 1 mVPP, and quiet during standing, with amplitudes less than 0.1 mVPP. RPNI signals were periodic and entrained with gait. A decoder predicted bilateral ankle motion with greater than 80% reliability. Control group signal activity agreed with literature. Denervated group signals remained quiescent throughout all evaluations. SIGNIFICANCE: In vivo myoelectric RPNI activity encodes neural activation patterns associated with gait. Signal contamination from muscles adjacent to the RPNI is minimal, as demonstrated by the low amplitude signals obtained from the Denervated group. The periodicity and entrainment to gait of RPNI recordings suggests the transduced signals were generated via central nervous system control.