A Highly Selective 3D Spiked Ultraflexible Neural (SUN) Interface for Decoding Peripheral Nerve Sensory Information

A Scoping Review of Machine Learning Applied to Peripheral Nerve Interfaces

Peripheral nerve interfaces (PNIs) can enable communication with the peripheral nervous system and have a broad range of applications including in bioelectronic medicine and neuroprostheses. They can modulate neural activity through stimulation or monitor conditions by recording from the peripheral nerves. The recent growth of Machine Learning (ML) has led to the application of a wide variety of ML techniques to PNIs, especially in circumstances where the goal is classification or regression. However, the extent to which ML has been applied to PNIs or the range of suitable ML techniques has not been documented. Therefore, a scoping review was conducted to determine and understand the state of ML in the PNI field. The review searched five databases and included 63 studies after full-text review. Most studies incorporated a supervised learning approach to classify activity, with the most common algorithms being some form of neural network (artificial neural network, convolutional neural network or recurrent neural network). Unsupervised, semi-supervised and reinforcement learning (RL) approaches are currently underutilized and could be better leveraged to improve performance in this domain.

Decoding bladder state from pudendal intraneural signals in pigs

Neuroprosthetic devices used for the treatment of lower urinary tract dysfunction, such as incontinence or urinary retention, apply a pre-set continuous, open-loop stimulation paradigm, which can cause voiding dysfunctions due to neural adaptation. In the literature, conditional, closed-loop stimulation paradigms have been shown to increase bladder capacity and voiding efficacy compared to continuous stimulation. Current limitations to the implementation of the closed-loop stimulation paradigm include the lack of robust and real-time decoding strategies for the bladder fullness state. We recorded intraneural pudendal nerve signals in five anesthetized pigs. Three bladder-filling states, corresponding to empty, full, and micturition, were decoded using the Random Forest classifier. The decoding algorithm showed a mean balanced accuracy above 86.67% among the three classes for all five animals. Our approach could represent an important step toward the implementation of an adaptive real-time closed-loop stimulation protocol for pudendal nerve modulation, paving the way for the design of an assisted-as-needed neuroprosthesis.

The Emergence of AI-Based Wearable Sensors for Digital Health Technology: A Review

Disease diagnosis and monitoring using conventional healthcare services is typically expensive and has limited accuracy. Wearable health technology based on flexible electronics has gained tremendous attention in recent years for monitoring patient health owing to attractive features, such as lower medical costs, quick access to patient health data, ability to operate and transmit data in harsh environments, storage at room temperature, non-invasive implementation, mass scaling, etc. This technology provides an opportunity for disease pre-diagnosis and immediate therapy. Wearable sensors have opened a new area of personalized health monitoring by accurately measuring physical states and biochemical signals. Despite the progress to date in the development of wearable sensors, there are still several limitations in the accuracy of the data collected, precise disease diagnosis, and early treatment. This necessitates advances in applied materials and structures and using artificial intelligence (AI)-enabled wearable sensors to extract target signals for accurate clinical decision-making and efficient medical care. In this paper, we review two significant aspects of smart wearable sensors. First, we offer an overview of the most recent progress in improving wearable sensor performance for physical, chemical, and biosensors, focusing on materials, structural configurations, and transduction mechanisms. Next, we review the use of AI technology in combination with wearable technology for big data processing, self-learning, power-efficiency, real-time data acquisition and processing, and personalized health for an intelligent sensing platform. Finally, we present the challenges and future opportunities associated with smart wearable sensors.

Artificial intelligence enhanced sensors - enabling technologies to next-generation healthcare and biomedical platform

The fourth industrial revolution has led to the development and application of health monitoring sensors that are characterized by digitalization and intelligence. These sensors have extensive applications in medical care, personal health management, elderly care, sports, and other fields, providing people with more convenient and real-time health services. However, these sensors face limitations such as noise and drift, difficulty in extracting useful information from large amounts of data, and lack of feedback or control signals. The development of artificial intelligence has provided powerful tools and algorithms for data processing and analysis, enabling intelligent health monitoring, and achieving high-precision predictions and decisions. By integrating the Internet of Things, artificial intelligence, and health monitoring sensors, it becomes possible to realize a closed-loop system with the functions of real-time monitoring, data collection, online analysis, diagnosis, and treatment recommendations. This review focuses on the development of healthcare artificial sensors enhanced by intelligent technologies from the aspects of materials, device structure, system integration, and application scenarios. Specifically, this review first introduces the great advances in wearable sensors for monitoring respiration rate, heart rate, pulse, sweat, and tears; implantable sensors for cardiovascular care, nerve signal acquisition, and neurotransmitter monitoring; soft wearable electronics for precise therapy. Then, the recent advances in volatile organic compound detection are highlighted. Next, the current developments of human-machine interfaces, AI-enhanced multimode sensors, and AI-enhanced self-sustainable systems are reviewed. Last, a perspective on future directions for further research development is also provided. In summary, the fusion of artificial intelligence and artificial sensors will provide more intelligent, convenient, and secure services for next-generation healthcare and biomedical applications.

Recent progress of electroactive interface in neural engineering

Neural tissue is an electrical responsible organ. The electricity plays a vital role in the growth and development of nerve tissue, as well as the repairing after diseases. The interface between the nervous system and external device for information transmission is called neural electroactive interface. With the development of new materials and fabrication technologies, more and more new types of neural interfaces are developed and the interfaces can play crucial roles in treating many debilitating diseases such as paralysis, blindness, deafness, epilepsy, and Parkinson's disease. Neural interfaces are developing toward flexibility, miniaturization, biocompatibility, and multifunctionality. This review presents the development of neural electrodes in terms of different materials for constructing electroactive neural interfaces, especially focus on the piezoelectric materials-based indirect neuromodulation due to their features of wireless control, excellent effect, and good biocompatibility. We discussed the challenges we need to consider before the application of these new interfaces in clinical practice. The perspectives about future directions for developing more practical electroactive interface in neural engineering are also discussed in this review. This article is categorized under: Implantable Materials and Surgical Technologies > Nanomaterials and Implants Implantable Materials and Surgical Technologies > Nanotechnology in Tissue Repair and Replacement.

Ultraflexible and Stretchable Intrafascicular Peripheral Nerve Recording Device with Axon-Dimension, Cuff-Less Microneedle Electrode Array

Peripheral nerve mapping tools with higher spatial resolution are needed to advance systems neuroscience, and potentially provide a closed-loop biomarker in neuromodulation applications. Two critical challenges of microscale neural interfaces are 1) how to apply them to small peripheral nerves, and 2) how to minimize chronic reactivity. A flexible microneedle nerve array (MINA) is developed, which is the first high-density penetrating electrode array made with axon-sized silicon microneedles embedded in low-modulus thin silicone. The design, fabrication, acute recording, and chronic reactivity to an implanted MINA, are presented. Distinctive units are identified in the rat peroneal nerve. The authors also demonstrate a long-term, cuff-free, and suture-free fixation manner using rose bengal as a light-activated adhesive for two time-points. The tissue response is investigated at 1-week and 6-week time-points, including two sham groups and two MINA-implanted groups. These conditions are quantified in the left vagus nerve of rats using histomorphometry. Micro computed tomography (micro-CT) is added to visualize and quantify tissue encapsulation around the implant. MINA demonstrates a reduction in encapsulation thickness over previously quantified interfascicular methods. Future challenges include techniques for precise insertion of the microneedle electrodes and demonstrating long-term recording.

Advanced Implantable Biomedical Devices Enabled by Triboelectric Nanogenerators

Implantable biomedical devices (IMDs) play essential roles in healthcare. Subject to the limited battery life, IMDs cannot achieve long-term in situ monitoring, diagnosis, and treatment. The proposal and rapid development of triboelectric nanogenerators free IMDs from the shackles of batteries and spawn a self-powered healthcare system. This review aims to overview the development of IMDs based on triboelectric nanogenerators, divided into self-powered biosensors, in vivo energy harvesting devices, and direct electrical stimulation therapy devices. Meanwhile, future challenges and opportunities are discussed according to the development requirements of current-level self-powered IMDs to enhance output performance, develop advanced triboelectric nanogenerators with multifunctional materials, and self-driven close-looped diagnosis and treatment systems.

Dense Packed Drivable Optrode Array for Precise Optical Stimulation and Neural Recording in Multiple-Brain Regions

The input-output function of neural networks is complicated due to the huge number of neurons and synapses, and some high-density implantable electrophysiology recording tools with a plane structure have been developed for neural circuit studies in recent years. However, traditional plane probes are limited by the record-only function and inability to monitor multiple-brain regions simultaneously, and the complete cognition of neural networks still has a long way away. Herein, we develop a three-dimensional (3D) high-density drivable optrode array for multiple-brain recording and precise optical stimulation simultaneously. The optrode array contains four-layer probes with 1024 microelectrodes and two thinned optical fibers assembled into a 3D-printed drivable module. The recording performance of microelectrodes is optimized by electrochemical modification, and precise implantation depth control of drivable optrodes is verified in agar. Moreover, in vivo experiments indicate neural activities from CA1 and dentate gyrus regions are monitored, and a tracking of the neuron firing for 2 weeks is achieved. The suppression of neuron firing by blue light has been realized through high-density optrodes during optogenetics experiments. With the feature of large-scale recording, optoelectronic integration, and 3D assembly, the high-density drivable optrode array possesses an important value in the research of brain diseases and neural networks.

A 3D flexible neural interface based on a microfluidic interconnection cable capable of chemical delivery

The demand for multifunctional neural interfaces has grown due to the need to provide a better understanding of biological mechanisms related to neurological diseases and neural networks. Direct intracerebral drug injection using microfluidic neural interfaces is an effective way to deliver drugs to the brain, and it expands the utility of drugs by bypassing the blood-brain barrier (BBB). In addition, uses of implantable neural interfacing devices have been challenging due to inevitable acute and chronic tissue responses around the electrodes, pointing to a critical issue still to be overcome. Although neural interfaces comprised of a collection of microneedles in an array have been used for various applications, it has been challenging to integrate microfluidic channels with them due to their characteristic three-dimensional structures, which differ from two-dimensionally fabricated shank-type neural probes. Here we present a method to provide such three-dimensional needle-type arrays with chemical delivery functionality. We fabricated a microfluidic interconnection cable (µFIC) and integrated it with a flexible penetrating microelectrode array (FPMA) that has a 3-dimensional structure comprised of silicon microneedle electrodes supported by a flexible array base. We successfully demonstrated chemical delivery through the developed device by recording neural signals acutely from in vivo brains before and after KCl injection. This suggests the potential of the developed microfluidic neural interface to contribute to neuroscience research by providing simultaneous signal recording and chemical delivery capabilities.

Triboelectric Nanogenerators for Therapeutic Electrical Stimulation

Current solutions developed for the purpose of in and on body (IOB) electrical stimulation (ES) lack autonomous qualities necessary for comfortable, practical, and self-dependent use. Consequently, recent focus has been placed on developing self-powered IOB therapeutic devices capable of generating therapeutic ES for human use. With the recent invention of the triboelectric nanogenerator (TENG), harnessing passive human biomechanical energy to develop self-powered systems has allowed for the introduction of novel therapeutic ES solutions. TENGs are especially effective at providing ES for IOB therapeutic systems given their bioconformability, low cost, simple manufacturability, and self-powering capabilities. Due to the key role of naturally induced electrical signals in many physiological functions, TENG-induced ES holds promise to provide a novel paradigm in therapeutic interventions. The aim here is to detail research on IOB TENG devices applied for ES-based therapy in the fields of regenerative medicine, neurology, rehabilitation, and pharmaceutical engineering. Furthermore, considering TENG-produced ES can be measured for sensing applications, this technology is paving the way to provide a fully autonomous personalized healthcare system, capable of IOB energy generation, sensing, and therapeutic intervention. Considering these grounds, it seems highly relevant to review TENG-ES research and applications, as they could constitute the foundation and future of personalized healthcare.

Biomedical and Tissue Engineering Strategies to Control Foreign Body Reaction to Invasive Neural Electrodes

Neural-interfaced prostheses aim to restore sensorimotor limb functions in amputees. They rely on bidirectional neural interfaces, which represent the communication bridge between nervous system and neuroprosthetic device by controlling its movements and evoking sensory feedback. Compared to extraneural electrodes (i.e., epineural and perineural implants), intraneural electrodes, implanted within peripheral nerves, have higher selectivity and specificity of neural signal recording and nerve stimulation. However, being implanted in the nerve, their main limitation is represented by the significant inflammatory response that the body mounts around the probe, known as Foreign Body Reaction (FBR), which may hinder their rapid clinical translation. Furthermore, the mechanical mismatch between the consistency of the device and the surrounding neural tissue may contribute to exacerbate the inflammatory state. The FBR is a non-specific reaction of the host immune system to a foreign material. It is characterized by an early inflammatory phase eventually leading to the formation of a fibrotic capsule around intraneural interfaces, which increases the electrical impedance over time and reduces the chronic interface biocompatibility and functionality. Thus, the future in the reduction and control of the FBR relies on innovative biomedical strategies for the fabrication of next-generation neural interfaces, such as the development of more suitable designs of the device with smaller size, appropriate stiffness and novel conductive and biomimetic coatings for improving their long-term stability and performance. Here, we present and critically discuss the latest biomedical approaches from material chemistry and tissue engineering for controlling and mitigating the FBR in chronic neural implants.

Flourishing energy harvesters for future body sensor network: from single to multiple energy sources

Body sensor network (bodyNET) offers possibilities for future disease diagnosis, preventive health care, rehabilitation, and treatment. However, the eventual realization demands reliable and sustainable power sources. The flourishing energy harvesters (EHs) have provided prominent techniques for practically addressing the concurrent energy issue. Targeting for a specific energy source, wearable EHs with a sole conversion mechanism are well investigated. Hybrid EHs integrating different effects for a single source or multi-sources are attaining growing attention, for they provide another degree of freedom concerning a higher-level energy utility. Merging EHs with other functional electronics, diversified functional self-sustainable systems are developed, paving the way for the accomplishment of bodyNET. This review introduces the evolution of wearable EHs from a single effect to hybridized mechanisms for multiple energy sources and wearable to implantable self-sustainable systems. Last, we provide our perspectives on the future development of hybrid EHs to be more competitive with conventional batteries.

W:Ti Flexible Transversal Electrode Array for Peripheral Nerve Stimulation: A Feasibility Study

The development of hardware for neural interfacing remains a technical challenge. We introduce a flexible, transversal intraneural tungsten:titanium electrode array for acute studies. We characterize the electrochemical properties of this new combination of tungsten and titanium using cyclic voltammetry and electrochemical impedance spectroscopy. With an in-vivo rodent study, we show that the stimulation of peripheral nerves with this electrode array is possible and that more than half of the electrode contacts can yield a stimulation selectivity index of 0.75 or higher at low stimulation currents. This feasibility study paves the way for the development of future cost-effective and easy-to-fabricate neural interfacing electrodes for acute settings, which ultimately can inform the development of technologies that enable bi-directional communication with the human nervous system.

Nanotunnels within Poly(3,4-ethylenedioxythiophene)-Carbon Nanotube Composite for Highly Sensitive Neural Interfacing

Neural electrodes are developed for direct communication with neural tissues for theranostics. Although various strategies have been employed to improve performance, creating an intimate electrode-tissue interface with high electrical fidelity remains a great challenge. Here, we report the rational design of a tunnel-like electrode coating comprising poly(3,4-ethylenedioxythiophene) (PEDOT) and carbon nanotubes (CNTs) for highly sensitive neural recording. The coated electrode shows a 50-fold reduction in electrochemical impedance at the biologically relevant frequency of 1 kHz, compared to the bare gold electrode. The incorporation of CNT significantly reinforces the nanotunnel structure and improves coating adhesion by ∼1.5 fold. In vitro primary neuron culture confirms an intimate contact between neurons and the PEDOT-CNT nanotunnel. During acute in vivo nerve recording, the coated electrode enables the capture of high-fidelity neural signals with low susceptibility to electrical noise and reveals the potential for precisely decoding sensory information through mechanical and thermal stimulation. These findings indicate that the PEDOT-CNT nanotunnel composite serves as an active interfacing material for neural electrodes, contributing to neural prosthesis and brain-machine interface.

Extracellular single-unit recordings from peripheral nerve axons in vitro by a novel multichannel microelectrode array

The peripheral nervous system (PNS) is an attractive target for modulation of afferent input (e.g., nociceptive input signaling tissue damage) to the central nervous system. To advance mechanistic understanding of PNS neural encoding and modulation requires single-unit recordings from individual peripheral neurons or axons. This is challenged by multiple connective tissue layers surrounding peripheral nerve fibers that prevent electrical recordings by existing electrodes or electrode arrays. In this study, we developed a novel microelectrode array (MEA) via silicon-based microfabrication that consists of 5 parallel hydrophilic gold electrodes surrounded by silanized hydrophobic surfaces. This novel hydrophilic/hydrophobic surface pattern guides the peripheral nerve filaments to self-align towards the hydrophilic electrodes, which dramatically reduces the technical challenges in conducting single-unit recordings. We validated our MEA by recording simultaneous single-unit action potentials from individual axons in mouse sciatic nerves, including both myelinated A-fibers and unmyelinated C-fibers. We confirmed that our recordings were single units from individual axons by increasing nerve trunk electrical stimulus intensity, which did not alter the spike shape or amplitude. By reducing the technical challenges, our novel MEA will likely allow peripheral single-unit recordings to be adopted by a larger research community and thus expedite our mechanistic understanding of peripheral neural encoding and modulation.

Classification of naturally evoked compound action potentials in peripheral nerve spatiotemporal recordings

Peripheral neural signals have the potential to provide the necessary motor, sensory or autonomic information for robust control in many neuroprosthetic and neuromodulation applications. However, developing methods to recover information encoded in these signals is a significant challenge. We introduce the idea of using spatiotemporal signatures extracted from multi-contact nerve cuff electrode recordings to classify naturally evoked compound action potentials (CAP). 9 Long-Evan rats were implanted with a 56-channel nerve cuff on the sciatic nerve. Afferent activity was selectively evoked in the different fascicles of the sciatic nerve (tibial, peroneal, sural) using mechano-sensory stimuli. Spatiotemporal signatures of recorded CAPs were used to train three different classifiers. Performance was measured based on the classification accuracy, F₁-score, and the ability to reconstruct original firing rates of neural pathways. The mean classification accuracies, for a 3-class problem, for the best performing classifier was 0.686 ± 0.126 and corresponding mean F₁-score was 0.605 ± 0.212. The mean Pearson correlation coefficients between the original firing rates and estimated firing rates found for the best classifier was 0.728 ± 0.276. The proposed method demonstrates the possibility of classifying individual naturally evoked CAPs in peripheral neural signals recorded from extraneural electrodes, allowing for more precise control signals in neuroprosthetic applications.

Investigation of Low-Current Direct Stimulation for Rehabilitation Treatment Related to Muscle Function Loss Using Self-Powered TENG System

Muscle function loss is characterized as abnormal or completely lost muscle capabilities, and it can result from neurological disorders or nerve injuries. The currently available clinical treatment is to electrically stimulate the diseased muscles. Here, a self-powered system of a stacked-layer triboelectric nanogenerator (TENG) and a multiple-channel epimysial electrode to directly stimulate muscles is demonstrated. Then, the two challenges regarding direct TENG muscle stimulation are further investigated. For the first challenge of improving low-current TENG stimulation efficiency, it is found that the optimum stimulation efficiency can be achieved by conducting a systematic mapping with a multiple-channel epimysial electrode. The second challenge is TENG stimulation stability. It is found that the force output generated by TENGs is more stable than using the conventional square wave stimulation and enveloped high frequency stimulation. With modelling and in vivo measurements, it is confirmed that the two factors that account for the stable stimulation using TENGs are the long pulse duration and low current amplitude. The current waveform of TENGs can effectively avoid synchronous motoneuron recruitment at the two stimulation electrodes to reduce force fluctuation. Here, after investigating these two challenges, it is believed that TENG direct muscle stimulation could be used for rehabilitative and therapeutic purpose of muscle function loss treatment.

Wire Electrodes Embedded in Artificial Conduit for Long-term Monitoring of the Peripheral Nerve Signal

Massive efforts to develop neural interfaces have been made for controlling prosthetic limbs according to the will of the patient, with the ultimate goal being long-term implantation. One of the major struggles is that the electrode’s performance degrades over time due to scar formation. Herein, we have developed peripheral nerve electrodes with a cone-shaped flexible artificial conduit capable of protecting wire electrodes from scar formation. The wire electrodes, which are composed of biocompatible alloy materials, were embedded in the conduit where the inside was filled with collagen to allow the damaged nerves to regenerate into the conduit and interface with the wire electrodes. After implanting the wire electrodes into the sciatic nerve of a rat, we successfully recorded the peripheral neural signals while providing mechanical stimulation. Remarkably, we observed the external stimuli-induced nerve signals at 19 weeks after implantation. This is possibly due to axon regeneration inside our platform. To verify the tissue response of our electrodes to the sciatic nerve, we performed immunohistochemistry (IHC) and observed axon regeneration without scar tissue forming inside the conduit. Thus, our strategy has proven that our neural interface can play a significant role in the long-term monitoring of the peripheral nerve signal.

Multilayer 3D electrodes for neural implants

OBJECTIVE

In many applications, multielectrode arrays employed as neural implants require a high density and a high number of electrodes to precisely record and stimulate the activity of the nervous system while preserving the overall size of the array.

APPROACH

Here we present a multilayer and three-dimensional (3D) electrode array, together with its manufacturing method, enabling a higher electrode density and a more efficient signal transduction with the biological tissue.

MAIN RESULTS

The 3D structure of the electrode array allows for a multilayer placement of the interconnects within a flexible substrate, it narrows the probe size per the same number of electrodes, and it maintains the electrode contacts at the same level within the tissue. In addition, it augments the electrode surface area, leading to a lower electrochemical impedance and a higher charge storage capacity. To characterize the recordings capabilities of the multilayer 3D electrodes, we measured visually evoked cortical potentials in mice and analysed the evolution of the peak prominences and latencies according to different light intensities and recording depths within the brain. The resulting signal-to-noise ratio is improved compared to flat electrodes. Finally, the 3D electrodes have been imaged inside a clarified mouse brain using a light-sheet microscope to visualize their integrity within the tissue.

SIGNIFICANCE

The multilayer 3D electrodes have proved to be a valid technology to ensure tissue proximity and higher recording/stimulating efficiencies while enabling higher electrode density and reducing the probe size.