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

Abstract

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.

Keywords: Amputees; Peripheral nerve Interface; Prosthetics; Regenerative medicine.

Conflict of interest statement

Ethics approval

All animal care and use procedures were conducted in accordance with the National Research Council’s Guide for the Care and Use of Laboratory Animals, (1996) and were approved by the University of Michigan Animal Care and Use Committee, under protocol number PRO00005717.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1

Left: Control group with primary repair of the extensor digitorum longus muscle (EDL) tenotomies without denervation of the muscle. Center: Denervated group with free EDL muscle graft performed to the lateral thigh. Neurotization and reinnervation was not performed, leaving the EDL muscle graft without innervation. Electrode placement was identical to the Control group. Right: Regenerative Peripheral Nerve Interface (RPNI) group with free EDL muscle graft performed to the lateral thigh. Neurotization and reinnervation were implemented using the peroneal nerve. Each rat received bipolar epimysial electrodes (white), whose wires (blue) were tunneled subcutaneously to the upper dorsum. a. bipolar electrode cables. b.tibialis anterior muscle; c. soleus and gastrocnemius muscles; d. distal end of common peroneal nerve; e. EDL muscle; f. proximal common peroneal nerve; g. tibial nerve

Fig. 2

EMG signals integrated over 300 msec (iEMG) – based prosthesis activation during one testing session. Plots of filtered EMG tracings (Blue) and periods of prosthesis activation (Green) during 40 s of testing in Control (Top), Denervated (Middle) and RPNI (Bottom) groups. Baseline iEMG is calculated as a running average. An algorithm activates the prosthesis after detecting an iEMG window more than 1 standard deviation above the mean iEMG

Fig. 3

Schematic showing acquisition, transduction and analysis of real-time recorded EMG signaling from an RPNI rat. a. Bipolar collection of raw EMG signals. Ground electrode is referenced in ear. b. Raw EMG signals undergo signal processing in the form of filtering and rectification. c. & d. 300 msec consecutive EMG signal acquisition intervals obtained during c. no observed leg motion (baseline signal activity below threshold), and d. Leg motion and subsequent prosthetic hand activation due to signal surpassing threshold of activation. Blue lines: EMG signal; Red lines: iEMG value; Green lines: Activation threshold

Fig. 4

A semi-logarithmic relationship between monofilament pressure applied and iEMG recorded during four testing blocks. Each block lasted 5 min for each increment of pressure increase in RPNI and Control groups (blue and orange, respectively). Monofilament pressure is graphed logarithmically to linearize each graph. Each represents the mean ± 1 SD for the average of 54 leg movements for control and 51 leg movements for RPNI per increment of pressure. Positive trends in both RPNI and Control groups imply RPNI transduced EMG signals of proportional intensity similar to that of an in situ Control

Fig. 5

Mean ± 1 Standard Deviation of iEMG values obtained during baseline (blue) and activation trials regardless of monofilament pressure (orange) in Control, Denervated and RPNI rat cohorts. iEMG is calculated as the area under the curve measured during consecutive 300 msec intervals of EMG signal acquisition during testing. Activated iEMG is recorded during rat movement while baseline iEMG is obtained during rest. † Denervated group as expected did not show activity during rat movement; therefore, no activated iEMG was calculated. A * indicates significantly higher activation signals, when compared with relative baseline signals within Control and RPNI groups (p < 0.05)