Clinical outcomes of peripheral nerve interfaces for rehabilitation in paralysis and amputation: a literature review

Peripheral nerve interfaces (PNIs) are electrical systems designed to integrate with peripheral nerves in patients, such as following central nervous system (CNS) injuries to augment or replace CNS control and restore function. We review the literature for clinical trials and studies containing clinical outcome measures to explore the utility of human applications of PNIs. We discuss the various types of electrodes currently used for PNI systems and their functionalities and limitations. We discuss important design characteristics of PNI systems, including biocompatibility, resolution and specificity, efficacy, and longevity, to highlight their importance in the current and future development of PNIs. The clinical outcomes of PNI systems are also discussed. Finally, we review relevant PNI clinical trials that were conducted, up to the present date, to restore the sensory and motor function of upper or lower limbs in amputees, spinal cord injury patients, or intact individuals and describe their significant findings. This review highlights the current progress in the field of PNIs and serves as a foundation for future development and application of PNI systems.

Examining the in vivo functionality of the Magnetically Aligned Regenerative Tissue-Engineered Electronic Nerve Interface (MARTEENI)

OBJECTIVE

Although neural-enabled prostheses have been used to restore some lost functionality in clinical trials, they have faced difficulty in achieving high degree of freedom, natural use compared to healthy limbs. This study investigated the in vivo functionality of a flexible and scalable regenerative peripheral-nerve interface suspended within a microchannel-embedded, tissue-engineered hydrogel (the Magnetically Aligned Regenerative Tissue-Engineered Electronic Nerve Interface, MARTEENI) as a potential approach to improving current issues in peripheral nerve interfaces.

APPROACH

Assembled MARTEENI devices were implanted in the gaps of severed sciatic nerves in Lewis rats. Both acute and chronic electrophysiology were recorded, and channel-isolated activity was examined. In terminal experiments, evoked activity during paw compression and stimulus response curves generated from proximal nerve stimulation were examined. Electrochemical impedance spectroscopy was performed to assess the complex impedance of recording sites during chronic data collection. Features of the foreign-body response in non-functional implants were examined using immunohistological methods.

MAIN RESULTS

Channel-isolated activity was observed in acute, chronic, and terminal experiments and showed a typically biphasic morphology with peak-to-peak amplitudes varying between 50 to 500 µV. For chronic experiments, electrophysiology was observed for 77 days post-implant. Within the templated hydrogel, regenerating axons formed minifascicles that varied in both size and axon count and were also found to surround device threads. No axons were found to penetrate the foreign-body response. Together these results suggest the MARTEENI is a promising approach for interfacing with peripheral nerves.

SIGNIFICANCE

Findings demonstrate a high likelihood that observed electrophysiological activity recorded from implanted MARTEENIs originated from neural tissue. The variation in minifascicle size seen histologically suggests that amplitude distributions observed in functional MARTEENIs may be due to a combination of individual axon and mini-compound action potentials. This study provided an assessment of a functional MARTEENI in an in vivo animal model for the first time.

Tutorial: A guide to techniques for analysing recordings from the peripheral nervous system

The nervous system, through a combination of conscious and automatic processes, enables the regulation of the body and its interactions with the environment. The peripheral nervous system is an excellent target for technologies that seek to modulate, restore or enhance these abilities as it carries sensory and motor information that most directly relates to a target organ or function. However, many applications require a combination of both an effective peripheral nerve interface and effective signal processing techniques to provide selective and stable recordings. While there are many reviews on the design of peripheral nerve interfaces, reviews of data analysis techniques and translational considerations are limited. Thus, this tutorial aims to support new and existing researchers in the understanding of the general guiding principles, and introduces a taxonomy for electrode configurations, techniques and translational models to consider.

The Need to Work Arm in Arm: Calling for Collaboration in Delivering Neuroprosthetic Limb Replacements

Over the last few decades there has been a push to enhance the use of advanced prosthetics within the fields of biomedical engineering, neuroscience, and surgery. Through the development of peripheral neural interfaces and invasive electrodes, an individual's own nervous system can be used to control a prosthesis. With novel improvements in neural recording and signal decoding, this intimate communication has paved the way for bidirectional and intuitive control of prostheses. While various collaborations between engineers and surgeons have led to considerable success with motor control and pain management, it has been significantly more challenging to restore sensation. Many of the existing peripheral neural interfaces have demonstrated success in one of these modalities; however, none are currently able to fully restore limb function. Though this is in part due to the complexity of the human somatosensory system and stability of bioelectronics, the fragmentary and as-yet uncoordinated nature of the neuroprosthetic industry further complicates this advancement. In this review, we provide a comprehensive overview of the current field of neuroprosthetics and explore potential strategies to address its unique challenges. These include exploration of electrodes, surgical techniques, control methods, and prosthetic technology. Additionally, we propose a new approach to optimizing prosthetic limb function and facilitating clinical application by capitalizing on available resources. It is incumbent upon academia and industry to encourage collaboration and utilization of different peripheral neural interfaces in combination with each other to create versatile limbs that not only improve function but quality of life. Despite the rapidly evolving technology, if the field continues to work in divided "silos," we will delay achieving the critical, valuable outcome: creating a prosthetic limb that is right for the patient and positively affects their life.

Deep Learning-Based Approaches for Decoding Motor Intent From Peripheral Nerve Signals

Previous literature shows that deep learning is an effective tool to decode the motor intent from neural signals obtained from different parts of the nervous system. However, deep neural networks are often computationally complex and not feasible to work in real-time. Here we investigate different approaches' advantages and disadvantages to enhance the deep learning-based motor decoding paradigm's efficiency and inform its future implementation in real-time. Our data are recorded from the amputee's residual peripheral nerves. While the primary analysis is offline, the nerve data is cut using a sliding window to create a “pseudo-online” dataset that resembles the conditions in a real-time paradigm. First, a comprehensive collection of feature extraction techniques is applied to reduce the input data dimensionality, which later helps substantially lower the motor decoder's complexity, making it feasible for translation to a real-time paradigm. Next, we investigate two different strategies for deploying deep learning models: a one-step (1S) approach when big input data are available and a two-step (2S) when input data are limited. This research predicts five individual finger movements and four combinations of the fingers. The 1S approach using a recurrent neural network (RNN) to concurrently predict all fingers' trajectories generally gives better prediction results than all the machine learning algorithms that do the same task. This result reaffirms that deep learning is more advantageous than classic machine learning methods for handling a large dataset. However, when training on a smaller input data set in the 2S approach, which includes a classification stage to identify active fingers before predicting their trajectories, machine learning techniques offer a simpler implementation while ensuring comparably good decoding outcomes to the deep learning ones. In the classification step, either machine learning or deep learning models achieve the accuracy and F1 score of 0.99. Thanks to the classification step, in the regression step, both types of models result in a comparable mean squared error (MSE) and variance accounted for (VAF) scores as those of the 1S approach. Our study outlines the trade-offs to inform the future implementation of real-time, low-latency, and high accuracy deep learning-based motor decoder for clinical applications.

Methods of integrating the human nervous system with electronic circuits

In recent years, many attempts have been made to connect electrical circuits with the human nervous system. The objective of type of research was diverse - from the desire to understand the physiology of the nervous system, through attempting to substitute nervous tissue defects with synthetic systems, to creating an interface that allows computers to be controlled directly with one's thought. Regardless of the original purpose, the creation of any form of such a combination would entail a series of subsequent discoveries, allowing for a real revolution in both theoretical and clinical neuroscience. Computers based on neurons, neurochips or mind prostheses are just some examples of technologies that could soon become part of everyday life. Despite numerous attempts, there is still no interface that meets all the expectations of the scholars. However, many scientific groups seem to be on the right track and their achievements raise extraordinary expectations. This paper evaluates historical theories and contemporary ideas about such interfaces to smoothly describe the major medical and scientific utility of the subject. Thus it presents the main issues surrounding the concept of integrating the human nervous system with electronic circuits.

Optical read-out and modulation of peripheral nerve activity

Numerous clinical and research applications necessitate the ability to interface with peripheral nerve fibers to read and control relevant neural pathways. Visceral organ modulation and rehabilitative prosthesis are two areas which could benefit greatly from improved neural interfacing approaches. Therapeutic neural interfacing, or ‘bioelectronic medicine’, has potential to affect a broad range of disorders given that all the major organs of the viscera are neurally innervated. However, a better understanding of the neural pathways that underlie function and a means to precisely interface with these fibers are required. Existing peripheral nerve interfaces, consisting primarily of electrode-based designs, are unsuited for highly specific (individual axon) communication and/or are invasive to the tissue. Our laboratory has explored an optogenetic approach by which optically sensitive reporters and actuators are targeted to specific cell (axon) types. The nature of such an approach is laid out in this short perspective, along with associated technologies and challenges.

Bionic intrafascicular interfaces for recording and stimulating peripheral nerve fibers

The network of peripheral nerves presents extraordinary potential for modulating and/or monitoring the functioning of internal organs or the brain. The degree to which these pathways can be used to influence or observe neural activity patterns will depend greatly on the quality and specificity of the bionic interface. The anatomical organization, which consists of multiple nerve fibers clustered into fascicles within a nerve bundle, presents opportunities and challenges that may necessitate insertion of electrodes into individual fascicles to achieve the specificity that may be required for many clinical applications. This manuscript reviews the current state-of-the-art in bionic intrafascicular interfaces, presents specific concerns for stimulation and recording, describes key implementation considerations and discusses challenges for future designs of bionic intrafascicular interfaces.

Time course study of long-term biocompatibility and foreign body reaction to intraneural polyimide-based implants

The foreign body reaction (FBR) against an implanted device is characterized by the formation of a fibrotic tissue around the implant. In the case of interfaces for peripheral nerves, used to stimulate specific group of axons and to record different nerve signals, the FBR induces a matrix deposition around the implant creating a physical separation between nerve fibers and the interface that may reduce its functionality over time. In order to understand how the FBR to intraneural interfaces evolves, polyimide non-functional devices were implanted in rat peripheral nerve. Functional tests (electrophysiological, pain and locomotion) and histological evaluation demonstrated that implanted devices did not cause any alteration in nerve function, in myelinated axons or in nerve architecture. The inflammatory response due to the surgical implantation decreased after 2 weeks. In contrast, inflammation was higher and more prolonged in the device implanted nerves with a peak after 2 weeks. With regard to tissue deposition, a tissue capsule appeared soon around the devices, acquiring maximal thickness at 2 weeks and being remodeled subsequently. Immunohistochemical analysis revealed two different cell types implicated in the FBR in the nerve: macrophages as the first cells in contact with the interface and fibroblasts that appear later at the edge of the capsule. Our results describe how the FBR against a polyimide implant in the peripheral nerve occurs and which are the main cellular players. Increasing knowledge of these responses will help to improve strategies to decrease the FBR against intraneural implants and to extend their usability. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 106A: 746-757, 2018.

Interfacing peripheral nerve with macro-sieve electrodes following spinal cord injury

Macro-sieve electrodes were implanted in the sciatic nerve of five adult male Lewis rats following spinal cord injury to assess the ability of the macro-sieve electrode to interface regenerated peripheral nerve fibers post-spinal cord injury. Each spinal cord injury was performed via right lateral hemisection of the cord at the T_9–10 site. Five months post-implantation, the ability of the macro-sieve electrode to interface the regenerated nerve was assessed by stimulating through the macro-sieve electrode and recording both electromyography signals and evoked muscle force from distal musculature. Electromyography measurements were recorded from the tibialis anterior and gastrocnemius muscles, while evoked muscle force measurements were recorded from the tibialis anterior, extensor digitorum longus, and gastrocnemius muscles. The macro-sieve electrode and regenerated sciatic nerve were then explanted for histological evaluation. Successful sciatic nerve regeneration across the macro-sieve electrode interface following spinal cord injury was seen in all five animals. Recorded electromyography signals and muscle force recordings obtained through macro-sieve electrode stimulation confirm the ability of the macro-sieve electrode to successfully recruit distal musculature in this injury model. Taken together, these results demonstrate the macro-sieve electrode as a viable interface for peripheral nerve stimulation in the context of spinal cord injury.

Regenerated Sciatic Nerve Axons Stimulated through a Chronically Implanted Macro-Sieve Electrode

Sieve electrodes provide a chronic interface for stimulating peripheral nerve axons. Yet, successful utilization requires robust axonal regeneration through the implanted electrode. The present study determined the effect of large transit zones in enhancing axonal regeneration and revealed an intimate neural interface with an implanted sieve electrode. Fabrication of the polyimide sieve electrodes employed sacrificial photolithography. The manufactured macro-sieve electrode (MSE) contained nine large transit zones with areas of ~0.285 mm² surrounded by eight Pt-Ir metallized electrode sites. Prior to implantation, saline, or glial derived neurotropic factor (GDNF) was injected into nerve guidance silicone-conduits with or without a MSE. The MSE assembly or a nerve guidance conduit was implanted between transected ends of the sciatic nerve in adult male Lewis rats. At 3 months post-operation, fiber counts were similar through both implant types. Likewise, stimulation of nerves regenerated through a MSE or an open silicone conduit evoked comparable muscle forces. These results showed that nerve regeneration was comparable through MSE transit zones and an open conduit. GDNF had a minimal positive effect on the quality and morphology of fibers regenerating through the MSE; thus, the MSE may reduce reliance on GDNF to augment axonal regeneration. Selective stimulation of several individual muscles was achieved through monopolar stimulation of individual electrodes sites suggesting that the MSE might be an optimal platform for functional neuromuscular stimulation.

Microelectrode array recordings from the ventral roots in chronically implanted cats

The ventral spinal roots contain the axons of spinal motoneurons and provide the only location in the peripheral nervous system where recorded neural activity can be assured to be motor rather than sensory. This study demonstrates recordings of single unit activity from these ventral root axons using floating microelectrode arrays (FMAs). Ventral root recordings were characterized by examining single unit yield and signal-to-noise ratios (SNR) with 32-channel FMAs implanted chronically in the L6 and L7 spinal roots of nine cats. Single unit recordings were performed for implant periods of up to 12 weeks. Motor units were identified based on active discharge during locomotion and inactivity under anesthesia. Motor unit yield and SNR were calculated for each electrode, and results were grouped by electrode site size, which were varied systematically between 25 and 160 μm to determine effects on signal quality. The unit yields and SNR did not differ significantly across this wide range of electrode sizes. Both SNR and yield decayed over time, but electrodes were able to record spikes with SNR >2 up to 12 weeks post-implant. These results demonstrate that it is feasible to record single unit activity from multiple isolated motor units with penetrating microelectrode arrays implanted chronically in the ventral spinal roots. This approach could be useful for creating a spinal nerve interface for advanced neural prostheses, and results of this study will be used to improve design of microelectrodes for chronic neural recording in the ventral spinal roots.