This manuscript provides an innovative method for developing a biologic peripheral nerve interface termed the Muscle Cuff Regenerative Peripheral Nerve Interface (MC-RPNI). This surgical construct can amplify its associated peripheral nerve’s motor efferent signals to facilitate accurate detection of motor intent and the potential control of exoskeleton devices.
Robotic exoskeletons have gained recent acclaim within the field of rehabilitative medicine as a promising modality for functional restoration for those individuals with extremity weakness. However, their use remains largely confined to research institutions, frequently operating as a means of static extremity support as motor detection methods remain unreliable. Peripheral nerve interfaces have arisen as a potential solution to this shortcoming; however, due to their inherently small amplitudes, these signals can be difficult to differentiate from background noise, lowering their overall motor detection accuracy. As current interfaces rely on abiotic materials, inherent material breakdown can occur alongside foreign body tissue reaction over time, further impacting their accuracy. The Muscle Cuff Regenerative Peripheral Nerve Interface (MC-RPNI) was designed to overcome these noted complications. Consisting of a segment of free muscle graft secured circumferentially to an intact peripheral nerve, the construct regenerates and becomes reinnervated by the contained nerve over time. In rats, this construct has demonstrated the ability to amplify a peripheral nerve’s motor efferent action potentials up to 100 times the normal value through the generation of compound muscle action potentials (CMAPs). This signal amplification facilitates high accuracy detection of motor intent, potentially enabling reliable utilization of exoskeleton devices.
In the United States alone, approximately 130 million people are affected by neuromuscular and musculoskeletal disorders, resulting in over $800 billion in annual economic impact1,2. This group of disorders is typically secondary to pathology within the nervous systems, at the neuromuscular junction, or within the muscle itself3. Despite the variety of pathologic origins, the majority share some degree of extremity weakness1,3. Unfortunately, this weakness is often permanent given the limitations in neural and muscle tissue regeneration, especially in the setting of severe trauma4,5,6.
Extremity weakness treatment algorithms have classically focused on rehabilitative and supportive measures, often relying on harnessing the capabilities of the remaining intact limbs (canes, wheelchairs, etc.)7. This strategy falls short, however, for those whose weakness is not limited to a single extremity. With recent innovations in robotic technologies, advanced exoskeleton devices have been developed that restore extremity functionality to those living with extremity weakness8,9,10,11,12,13. These robotic exoskeletons are often powered, wearable devices that can assist with initiation and termination of movement or maintenance of limb position, providing a varying amount of force that can be individually tailored for the user8,9,10,11,12,13. These devices are classified as either passive or active depending on how they provide motor assistance to the user: active devices contain electrical actuators that augment power to the user, whereas passive devices store energy from the user's motions in order to release it back to the user when necessary14. As active devices have the ability to increase a user's power capabilities, these devices are utilized far more frequently in the setting of extremity weakness[14].
In order to determine motor intent in this population, modern exoskeletons commonly rely on pattern recognition algorithms generated from either electromyography (EMG) of distal limb muscles8,15,16,17 or surface electroencephalography (sEEG) of the brain18,19,20. Despite the promise of these detection modalities, both options have significant limitations that preclude widespread utilization of these devices. As sEEG detects microvolt-level signals transcranially18,19,20, criticisms frequently focus on the inability to differentiate these signals from background noise21. When background noise is similar to the desired recording signal, this produces low signal-to-noise ratios (SNRs), resulting in inaccurate motor detection and classification22,23. Accurate signal detection additionally relies on stable, low-impedance scalp contact21, which can be significantly affected by the presence of coarse/thick hair, user activity, and even sweating22,24. In contrast, EMG signals are several magnitudes larger in amplitude, facilitating greater motor signal detection accuracy15,18,25. This comes at a cost, however, as nearby muscles can contaminate the signal, decreasing the degrees of freedom able to be controlled by the device16,17,25 and an inability to detect deep muscle motion25,26,27,28. Most importantly, EMG cannot be used as a control method when there is significant muscle compromise and complete absence of tissue29.
In order to advance the development of robotic exoskeletons, consistent and accurate detection of motor intent of the intended user is required. Interfaces that utilize the peripheral nervous system have arisen as a promising interface technique, given their relatively simple access and functional selectivity. Current peripheral nerve interfacing methods can be invasive or non-invasive and typically fall within one of three categories: extraneural electrodes30,31,32,33, intrafascicular electrodes34,35,36 and penetrating electrodes37,38,39,40. As peripheral nerve signals are generally on the level of microvolts, it can be difficult to differentiate these signals from similar amplitude background noise41,42, which reduces the overall motor detection accuracy capabilities of the interface. These low signal-to-noise (SNR) ratios often worsen over time secondary to worsening electrode impedance43 produced from either degradation of the device39,43, or local foreign body reaction producing scar tissue around the device and/or local axonal degeneration37,44. Although these shortcomings can generally be resolved with reoperation and implantation of a new peripheral nerve interface, this is not a viable long-term solution as foreign-body-associated reactions would continue to occur.
To avoid these local tissue reactions generated from peripheral nerves' interaction with abiotic interfaces, an interface incorporating a biologic component is necessary. To address this shortcoming, the Regenerative Peripheral Nerve Interface (RPNI) was developed to integrate transected peripheral nerves in the residual limbs of those with amputations with prosthetic devices45,46,47,48. Fabrication of the RPNI involves surgical implantation of a transected peripheral nerve into a segment of autologous free muscle graft, with revascularization, regeneration, and reinnervation occurring over time. Through the generation of milli-volt level compound muscle action potentials (CMAPs), the RPNI is able to amplify its contained nerve's micro-volt level signal by several magnitudes, facilitating accurate detection of motor intent45,48,49. There has been considerable development of the RPNI over the past decade, with notable success in amplifying and transmitting efferent motor nerve signals in both animal50,51 and human47 trials, facilitating high accuracy prosthetic device control with multiple degrees of freedom.
Individuals with extremity weakness but intact peripheral nerves would similarly benefit from high accuracy detection of motor intent through peripheral nerve interfaces in order to control exoskeleton devices. As the RPNI was developed for integration with transected peripheral nerves, such as in persons with amputations, surgical modifications were necessary. Building from experience with the RPNI, the Muscle Cuff Regenerative Peripheral Nerve Interface (MC-RPNI) was developed. Consisting of a similar segment of free muscle graft as in the RPNI, it is instead secured circumferentially to an intact peripheral nerve (Figure 1). Over time, it regenerates and becomes reinnervated through collateral axonal sprouting, amplifying and translating these efferent motor nerve signals to EMG signals that are several orders of magnitude larger52. As the MC-RPNI is biologic in origin, it avoids the inevitable foreign body reaction that occurs with peripheral nerve interfaces currently in use52. Furthermore, the MC-RPNI confers the ability to control multiple degrees of freedom simultaneously as they can be placed on distally dissected nerves to individual muscles without significant cross-talk, as has been previously demonstrated in RPNIs49. Finally, the MC-RPNI can operate independent of distal muscle function as it is placed on the proximal nerve. Given its advantages over current peripheral nerve interfaces, the MC-RPNI holds substantial promise for providing a safe, accurate, and reliable method of exoskeleton control.
The MC-RPNI is a novel construct that allows for amplification of an intact, peripheral motor nerve's efferent action potentials in order to accurately control an exoskeleton device. Specifically, the MC-RPNI confers a particular benefit to those individuals with extremity weakness caused by significant muscle disease and/or absence of muscle where EMG signals cannot be recorded. Reducing already compromised muscle function would be devastating in this population; however, the MC-RPNI has the ability to provide this …
The authors have nothing to disclose.
The authors thank Jana Moon for her expert lab management and technical assistance and Charles Hwang for his imaging expertise. Experiments in this paper were in part funded through Plastic Surgery Foundation grants to SS (3135146.4) as well as the National Institute of Child Health and Human Development under Award Number 1F32HD100286-01 to SS, and the National Institute of Arthritis and Musculoskeletal and Skin Diseases of the National Institutes of Health under Award Number P30 AR069620.
#15 Scalpel | Aspen Surgical, Inc | Ref 371115 | Rib-Back Carbon Steel Surgical Blades (#15) |
2-N-thin film load cell (S100) | Strain Measurement Devices, Inc | SMD100-0002 | Measures force generated by the attached muscle |
4-0 Chromic Suture | Ethicon | SKU# 1654G | P-3 Reverse Cutting Needle |
5-0 Chromic Suture | Ethicon | SKU# 687G | P-3 Reverse Cutting Needle |
8-0 Monofilament Suture | AROSurgical | T06A08N14-13 | Black polyamide monofilament suture on a threaded tapered needle |
Experimental Rats | Envigo | F344-NH-sd | Rats are Fischer F344 Strain |
Fine Forceps – mirror finish | Fine Science Tools | 11413-11 | Fine tipped forceps with mirror finish ideal for handling delicate structures like nerves |
Fluriso (Isofluorane) | VetOne | 13985-528-40 | Inhalational Anesthetic |
Force Measurement Jig | Red Rock | n/a | Custom designed force measurement jig that allows for immobilization of hindlimb to allow for accurate muscle force recording |
MATLAB software | Mathworks, Inc | PR-MATLAB-MU-MW-707-NNU | Calculates active force for each recorded force trace from passive and total force measurements |
Nicolet Viasys EMG EP System | Nicolet | MFI-NCL-VIKING-SELECT-2CH-EMG | Portable EMG and nerve signal recording system capable of simultaneous 2 channel recordings from nerve and/or muscle |
Oxygen | Cryogenic Gases | UN1072 | Standard medical grade oxygen canisters |
Potassium Chloride | APP Pharmaceuticals | 63323-965-20 | Injectable form, 2 mEq/mL |
Povidone Iodine USP | MediChoice | 65517-0009-1 | 10% Topical Solution, can use one bottle for multiple surgical preps |
Puralube Vet Opthalmic Ointment | Dechra | 17033-211-38 | Corneal protective ointment for use during procedure |
Rimadyl (Caprofen) | Zoetis, Inc. | NADA# 141-199 | Injectable form, 50 mg/mL |
Stereo Microscope | Leica | Model M60 | User can adjust magnification to their preference |
Surgical Instruments | Fine Science Tools | Various | User can choose instruments according to personal preference or from what is currently available in their lab |
Triple Antibiotic Ointment | MediChoice | 39892-0830-2 | Ointment comes in sterile, disposable packets |
Vannas Spring Scissors – 2mm cutting edge | Fine Science Tools | 15000-04 | Curved micro-dissection scissors used to perform the epineurial window |
VaporStick 3 | Surgivet | V7015 | Anesthesia tower with space for isofluorane and oxygen canister |
Webcol Alcohol Prep | Coviden | Ref 6818 | Alcohol prep wipes; use a new wipe for each prep |