Restoration of motor control and proprioceptive and cutaneous sensation in humans with prior upper-limb amputation via multiple Utah Slanted Electrode Arrays (USEAs) implanted in residual peripheral arm nerves

Intravascular delivery of an ultraflexible neural electrode array for recordings of cortical spiking activity

Although intracranial neural electrodes have significantly contributed to both fundamental research and clinical treatment of neurological diseases, their implantation requires invasive surgery to open craniotomies, which can introduce brain damage and disrupt normal brain functions. Recent emergence of endovascular neural devices offers minimally invasive approaches for neural recording and stimulation. However, existing endovascular neural devices are unable to resolve single-unit activity in large animal models or human patients, impeding a broader application as neural interfaces in clinical practice. Here, we present the ultraflexible implantable neural electrode as an intravascular device (uFINE-I) for recording brain activity at single-unit resolution. We successfully implanted uFINE-Is into the sheep occipital lobe by penetrating through the confluence of sinuses and recorded both local field potentials (LFPs) and multi-channel single-unit spiking activity under spontaneous and visually evoked conditions. Imaging and histological analysis revealed minimal tissue damage and immune response. The uFINE-I provides a practical solution for achieving high-resolution neural recording with minimal invasiveness and can be readily transferred to clinical settings for future neural interface applications such as brain-machine interfaces (BMIs) and the treatment of neurological diseases.

Clinical Applications and Future Translation of Somatosensory Neuroprostheses

Somatosensory neuroprostheses restore, replace, or enhance tactile and proprioceptive feedback for people with sensory impairments due to neurological disorders or injury. Somatosensory neuroprostheses typically couple sensor inputs from a wearable device, prosthesis, robotic device, or virtual reality system with electrical stimulation applied to the somatosensory nervous system via noninvasive or implanted interfaces. While prior research has mainly focused on technology development and proof-of-concept studies, recent acceleration of clinical studies in this area demonstrates the translational potential of somatosensory neuroprosthetic systems. In this review, we provide an overview of neurostimulation approaches currently undergoing human testing and summarize recent clinical findings on the perceptual, functional, and psychological impact of somatosensory neuroprostheses. We also cover current work toward the development of advanced stimulation paradigms to produce more natural and informative sensory feedback. Finally, we provide our perspective on the remaining challenges that need to be addressed prior to translation of somatosensory neuroprostheses.

Sensory integration for neuroprostheses: from functional benefits to neural correlates

In the field of sensory neuroprostheses, one ultimate goal is for individuals to perceive artificial somatosensory information and use the prosthesis with high complexity that resembles an intact system. To this end, research has shown that stimulation-elicited somatosensory information improves prosthesis perception and task performance. While studies strive to achieve sensory integration, a crucial phenomenon that entails naturalistic interaction with the environment, this topic has not been commensurately reviewed. Therefore, here we present a perspective for understanding sensory integration in neuroprostheses. First, we review the engineering aspects and functional outcomes in sensory neuroprosthesis studies. In this context, we summarize studies that have suggested sensory integration. We focus on how they have used stimulation-elicited percepts to maximize and improve the reliability of somatosensory information. Next, we review studies that have suggested multisensory integration. These works have demonstrated that congruent and simultaneous multisensory inputs provided cognitive benefits such that an individual experiences a greater sense of authority over prosthesis movements (i.e., agency) and perceives the prosthesis as part of their own (i.e., ownership). Thereafter, we present the theoretical and neuroscience framework of sensory integration. We investigate how behavioral models and neural recordings have been applied in the context of sensory integration. Sensory integration models developed from intact-limb individuals have led the way to sensory neuroprosthesis studies to demonstrate multisensory integration. Neural recordings have been used to show how multisensory inputs are processed across cortical areas. Lastly, we discuss some ongoing research and challenges in achieving and understanding sensory integration in sensory neuroprostheses. Resolving these challenges would help to develop future strategies to improve the sensory feedback of a neuroprosthetic system.

Realizing Upper Extremity Bionic Limbs: Leveraging Neuroprosthetic Control Strategies

SUMMARY

Innovations in prosthetic devices and neuroprosthetic control strategies have opened new frontiers for the treatment and rehabilitation of individuals undergoing amputation. Commercial prosthetic devices are now available with sophisticated electrical and mechanical components that can closely replicate the functions of the human musculoskeletal system. However, to truly recognize the potential of such prosthetic devices and develop the next generation of bionic limbs, a highly reliable prosthetic device control strategy is required. In the past few years, refined surgical techniques have enabled neuroprosthetic control strategies to record efferent motor and stimulate afferent sensory action potentials from a residual limb with extraordinary specificity, signal quality, and long-term stability. As a result, such control strategies are now capable of facilitating intuitive, real-time, and naturalistic prosthetic experiences for patients with amputations. This article summarizes the current state of upper extremity neuroprosthetic devices and discusses the leading control strategies that are critical to the ongoing advancement of prosthetic development and implementation.

Validity and Impact of Methods for Collecting Training Data for Myoelectric Prosthetic Control Algorithms

Intuitive regression control of prostheses relies on training algorithms to correlate biological recordings to motor intent. The quality of the training dataset is critical to run-time regression performance, but accurately labeling intended hand kinematics after hand amputation is challenging. In this study, we quantified the accuracy and precision of labeling hand kinematics using two common training paradigms: 1) mimic training, where participants mimic predetermined motions of a prosthesis, and 2) mirror training, where participants mirror their contralateral intact hand during synchronized bilateral movements. We first explored this question in healthy non-amputee individuals where the ground-truth kinematics could be readily determined using motion capture. Kinematic data showed that mimic training fails to account for biomechanical coupling and temporal changes in hand posture. Additionally, mirror training exhibited significantly higher accuracy and precision in labeling hand kinematics. These findings suggest that the mirror training approach generates a more faithful, albeit more complex, dataset. Accordingly, mirror training resulted in significantly better offline regression performance when using a large amount of training data and a non-linear neural network. Next, we explored these different training paradigms online, with a cohort of unilateral transradial amputees actively controlling a prosthesis in real-time to complete a functional task. Overall, we found that mirror training resulted in significantly faster task completion speeds and similar subjective workload. These results demonstrate that mirror training can potentially provide more dexterous control through the utilization of task-specific, user-selected training data. Consequently, these findings serve as a valuable guide for the next generation of myoelectric and neuroprostheses leveraging machine learning to provide more dexterous and intuitive control.

Neural population dynamics reveals disruption of spinal circuits' responses to proprioceptive input during electrical stimulation of sensory afferents

While neurostimulation technologies are rapidly approaching clinical applications for sensorimotor disorders, the impact of electrical stimulation on network dynamics is still unknown. Given the high degree of shared processing in neural structures, it is critical to understand if neurostimulation affects functions that are related to, but not targeted by, the intervention. Here, we approach this question by studying the effects of electrical stimulation of cutaneous afferents on unrelated processing of proprioceptive inputs. We recorded intraspinal neural activity in four monkeys while generating proprioceptive inputs from the radial nerve. We then applied continuous stimulation to the radial nerve cutaneous branch and quantified the impact of the stimulation on spinal processing of proprioceptive inputs via neural population dynamics. Proprioceptive pulses consistently produce neural trajectories that are disrupted by concurrent cutaneous stimulation. This disruption propagates to the somatosensory cortex, suggesting that electrical stimulation can perturb natural information processing across the neural axis.

Biomimetic computer-to-brain communication enhancing naturalistic touch sensations via peripheral nerve stimulation

Artificial communication with the brain through peripheral nerve stimulation shows promising results in individuals with sensorimotor deficits. However, these efforts lack an intuitive and natural sensory experience. In this study, we design and test a biomimetic neurostimulation framework inspired by nature, capable of "writing" physiologically plausible information back into the peripheral nervous system. Starting from an in-silico model of mechanoreceptors, we develop biomimetic stimulation policies. We then experimentally assess them alongside mechanical touch and common linear neuromodulations. Neural responses resulting from biomimetic neuromodulation are consistently transmitted towards dorsal root ganglion and spinal cord of cats, and their spatio-temporal neural dynamics resemble those naturally induced. We implement these paradigms within the bionic device and test it with patients (ClinicalTrials.gov identifier NCT03350061). He we report that biomimetic neurostimulation improves mobility (primary outcome) and reduces mental effort (secondary outcome) compared to traditional approaches. The outcomes of this neuroscience-driven technology, inspired by the human body, may serve as a model for advancing assistive neurotechnologies.

Development of a feline model for preclinical research of a new translabyrinthine auditory nerve implant

Cochlear implants are among the most successful neural prosthetic devices to date but exhibit poor frequency selectivity and the inability to consistently activate apical (low frequency) spiral ganglion neurons. These issues can limit hearing performance in many cochlear implant patients, especially for understanding speech in noisy environments and in perceiving or appreciating more complex inputs such as music and multiple talkers. For cochlear implants, electrical current must pass through the bony wall of the cochlea, leading to widespread activation of auditory nerve fibers. Cochlear implants also cannot be implanted in some individuals with an obstruction or severe malformations of the cochlea. Alternatively, intraneural stimulation delivered via an auditory nerve implant could provide direct contact with neural fibers and thus reduce unwanted current spread. More confined current during stimulation can increase selectivity of frequency fiber activation. Furthermore, devices such as the Utah Slanted Electrode Array can provide access to the full cross section of the auditory nerve, including low frequency fibers that are difficult to reach using a cochlear implant. However, further scientific and preclinical research of these Utah Slanted Electrode Array devices is limited by the lack of a chronic large animal model for the auditory nerve implant, especially one that leverages an appropriate surgical approach relevant for human translation. This paper presents a newly developed transbullar translabyrinthine surgical approach for implanting the auditory nerve implant into the cat auditory nerve. In our first of a series of studies, we demonstrate a surgical approach in non-recovery experiments that enables implantation of the auditory nerve implant into the auditory nerve, without damaging the device and enabling effective activation of the auditory nerve fibers, as measured by electrode impedances and electrically evoked auditory brainstem responses. These positive results motivate performing future chronic cat studies to assess the long-term stability and function of these auditory nerve implant devices, as well as development of novel stimulation strategies that can be translated to human patients.

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.

Neuromorphic hardware for somatosensory neuroprostheses

In individuals with sensory-motor impairments, missing limb functions can be restored using neuroprosthetic devices that directly interface with the nervous system. However, restoring the natural tactile experience through electrical neural stimulation requires complex encoding strategies. Indeed, they are presently limited in effectively conveying or restoring tactile sensations by bandwidth constraints. Neuromorphic technology, which mimics the natural behavior of neurons and synapses, holds promise for replicating the encoding of natural touch, potentially informing neurostimulation design. In this perspective, we propose that incorporating neuromorphic technologies into neuroprostheses could be an effective approach for developing more natural human-machine interfaces, potentially leading to advancements in device performance, acceptability, and embeddability. We also highlight ongoing challenges and the required actions to facilitate the future integration of these advanced technologies.

Electrical Stimulation of Regenerative Peripheral Nerve Interfaces (RPNIs) Induces Referred Sensations in People With Upper Limb Loss

Individuals with upper limb loss lack sensation of the missing hand, which can negatively impact their daily function. Several groups have attempted to restore this sensation through electrical stimulation of residual nerves. The purpose of this study was to explore the utility of regenerative peripheral nerve interfaces (RPNIs) in eliciting referred sensation. In four participants with upper limb loss, we characterized the quality and location of sensation elicited through electrical stimulation of RPNIs over time. We also measured functional stimulation ranges (sensory perception and discomfort thresholds), sensitivity to changes in stimulation amplitude, and ability to differentiate objects of different stiffness and sizes. Over a period of up to 54 months, stimulation of RPNIs elicited sensations that were consistent in quality (e.g. tingling, kinesthesia) and were perceived in the missing hand and forearm. The location of elicited sensation was partially-stable to stable in 13 of 14 RPNIs. For 5 of 7 RPNIs tested, participants demonstrated a sensitivity to changes in stimulation amplitude, with an average just noticeable difference of 45 nC. In a case study, one participant was provided RPNI stimulation proportional to prosthetic grip force. She identified four objects of different sizes and stiffness with 56% accuracy with stimulation alone and 100% accuracy when stimulation was combined with visual feedback of hand position. Collectively, these experiments suggest that RPNIs have the potential to be used in future bi-directional prosthetic systems.

System of Implantable Electrodes for Neural Signal Acquisition and Stimulation for Wirelessly Connected Forearm Prosthesis

There is great interest in the development of prosthetic limbs capable of complex activities that are wirelessly connected to the patient's neural system. Although some progress has been achieved in this area, one of the main problems encountered is the selective acquisition of nerve impulses and the closing of the automation loop through the selective stimulation of the sensitive branches of the patient. Large-scale research and development have achieved so-called "cuff electrodes"; however, they present a big disadvantage: they are not selective. In this article, we present the progress made in the development of an implantable system of plug neural microelectrodes that relate to the biological nerve tissue and can be used for the selective acquisition of neuronal signals and for the stimulation of specific nerve fascicles. The developed plug electrodes are also advantageous due to their small thickness, as they do not trigger nerve inflammation. In addition, the results of the conducted tests on a sous scrofa subject are presented.

Cortical Reorganization after Limb Loss: Bridging the Gap between Basic Science and Clinical Recovery

Despite the increasing incidence and prevalence of amputation across the globe, individuals with acquired limb loss continue to struggle with functional recovery and chronic pain. A more complete understanding of the motor and sensory remodeling of the peripheral and central nervous system that occurs postamputation may help advance clinical interventions to improve the quality of life for individuals with acquired limb loss. The purpose of this article is to first provide background clinical context on individuals with acquired limb loss and then to provide a comprehensive review of the known motor and sensory neural adaptations from both animal models and human clinical trials. Finally, the article bridges the gap between basic science researchers and clinicians that treat individuals with limb loss by explaining how current clinical treatments may restore function and modulate phantom limb pain using the underlying neural adaptations described above. This review should encourage the further development of novel treatments with known neurological targets to improve the recovery of individuals postamputation.Significance Statement In the United States, 1.6 million people live with limb loss; this number is expected to more than double by 2050. Improved surgical procedures enhance recovery, and new prosthetics and neural interfaces can replace missing limbs with those that communicate bidirectionally with the brain. These advances have been fairly successful, but still most patients experience persistent problems like phantom limb pain, and others discontinue prostheses instead of learning to use them daily. These problematic patient outcomes may be due in part to the lack of consensus among basic and clinical researchers regarding the plasticity mechanisms that occur in the brain after amputation injuries. Here we review results from clinical and animal model studies to bridge this clinical-basic science gap.

Characterization of perception by transcutaneous electrical Stimulation in terms of tingling intensity and temporal dynamics

Electrotactile feedback is a cost-effective and versatile method to provide new information or to augment intrinsic tactile feedback. As tactile feedback provides critical information for human-environment interaction, electrotactile feedback, accordingly, has many purposes to improve the quality of human-environment interaction in both direct and remote settings. However, electrotactile feedback overlays tingling sensation on top of the natural tactile feedback. To better characterize electrotactile feedback and understand the origin of the tingling sensation, a need arises to characterize the human perception of electrotactile feedback qualitatively and quantitatively, while varying the key stimulation parameters, namely amplitude and frequency. This study consists of two experiments. In the first experiment, the voltage for each subject was characterized by setting perception and discomfort thresholds. In the second experiment, subjects received electrical stimulation in 9 different combinations of voltages and frequencies. On delivering stimulation with each parameter combination, subjects reported their perception in two comparative scales-pressure vs. tingling and constant vs. pulsing. Subjects also reported the location of perception for stimulation with every parameter combination. More tingling and less pressure was reported as frequency increased, while the tingling-pressure percept was not affected by the amplitude change. Additionally, less pulsing and more constant was reported as frequency increased, while the pulsing-constant percept was not affected by the amplitude change. Concurrently, the normalized level of voltage thresholds was decreased as frequency increased. Dependency of tingling-pressure percept on stimulation frequency suggests that incongruency between the stimulation frequency and the natural firing rate of the sensory neuron would be an important factor of the tingling sensation. This study is a steppingstone to further demystify the origin of the tingling percept caused by electrical stimulation, thus broadening the use of transcutaneous electrical stimulation as a way of providing tactile cue or augmentation.

Selective recording of physiologically evoked neural activity in a mixed autonomic nerve using a minimally invasive array

Real-time closed-loop control of neuromodulation devices requires long-term monitoring of neural activity in the peripheral nervous system. Although many signal extraction methods exist, few are both clinically viable and designed for extracting small signals from fragile peripheral visceral nerves. Here, we report that our minimally invasive recording and analysis technology extracts low to negative signal to noise ratio (SNR) neural activity from a visceral nerve with a high degree of specificity for fiber type and class. Complex activity was recorded from the rat pelvic nerve that was physiologically evoked during controlled bladder filling and voiding, in an extensively characterized in vivo model that provided an excellent test bed to validate our technology. Urethane-anesthetized male rats (n = 12) were implanted with a four-electrode planar array and the bladder instrumented for continuous-flow cystometry, which measures urodynamic function by recording bladder pressure changes during constant infusion of saline. We demonstrated that differential bipolar recordings and cross-correlation analyses extracts afferent and efferent activity, and discriminated between subpopulations of fibers based on conduction velocity. Integrated Aδ afferent fiber activity correlated with bladder pressure during voiding (r2: 0.66 ± 0.06) and was not affected by activating nociceptive afferents with intravesical capsaicin (r2: 0.59 ± 0.14, P = 0.54, and n = 3). Collectively, these results demonstrate our minimally invasive recording and analysis technology is selective in extracting mixed neural activity with low/negative SNR. Furthermore, integrated afferent activity reliably correlates with bladder pressure and is a promising first step in developing closed-loop technology for bladder control.

Sensory Restoration for Improved Motor Control of Prostheses

Somatosensory neuroprostheses are devices with the potential to restore the senses of touch and movement from prosthetic limbs for people with limb amputation or paralysis. By electrically stimulating the peripheral or central nervous system, these devices evoke sensations that appear to emanate from the missing or insensate limb, and when paired with sensors on the prosthesis, they can improve the functionality and embodiment of the prosthesis. There have been major advances in the design of these systems over the past decade, although several important steps remain before they can achieve widespread clinical adoption outside the lab setting. Here, we provide a brief overview of somatosensory neuroprostheses and explores these hurdles and potential next steps towards clinical translation.

The Fifth Bioelectronic Medicine Summit: today's tools, tomorrow's therapies

The emerging field of bioelectronic medicine (BEM) is poised to make a significant impact on the treatment of several neurological and inflammatory disorders. With several BEM therapies being recently approved for clinical use and others in late-phase clinical trials, the 2022 BEM summit was a timely scientific meeting convening a wide range of experts to discuss the latest developments in the field. The BEM Summit was held over two days in New York with more than thirty-five invited speakers and panelists comprised of researchers and experts from both academia and industry. The goal of the meeting was to bring international leaders together to discuss advances and cultivate collaborations in this emerging field that incorporates aspects of neuroscience, physiology, molecular medicine, engineering, and technology. This Meeting Report recaps the latest findings discussed at the Meeting and summarizes the main developments in this rapidly advancing interdisciplinary field. Our hope is that this Meeting Report will encourage researchers from academia and industry to push the field forward and generate new multidisciplinary collaborations that will form the basis of new discoveries that we can discuss at the next BEM Summit.

Neural Decoding for Intracortical Brain-Computer Interfaces

Brain-computer interfaces have revolutionized the field of neuroscience by providing a solution for paralyzed patients to control external devices and improve the quality of daily life. To accurately and stably control effectors, it is important for decoders to recognize an individual's motor intention from neural activity either by noninvasive or intracortical neural recording. Intracortical recording is an invasive way of measuring neural electrical activity with high temporal and spatial resolution. Herein, we review recent developments in neural signal decoding methods for intracortical brain-computer interfaces. These methods have achieved good performance in analyzing neural activity and controlling robots and prostheses in nonhuman primates and humans. For more complex paradigms in motor rehabilitation or other clinical applications, there remains more space for further improvements of decoders.

Tessellation of artificial touch via microstimulation of human somatosensory cortex

When we interact with objects, we rely on signals from the hand that convey information about the object and our interaction with it. A basic feature of these interactions, the locations of contacts between the hand and object, is often only available via the sense of touch. Information about locations of contact between a brain-controlled bionic hand and an object can be signaled via intracortical microstimulation (ICMS) of somatosensory cortex (S1), which evokes touch sensations that are localized to a specific patch of skin. To provide intuitive location information, tactile sensors on the robotic hand drive ICMS through electrodes that evoke sensations at skin locations matching sensor locations. This approach requires that ICMS-evoked sensations be focal, stable, and distributed over the hand. To systematically investigate the localization of ICMS-evoked sensations, we analyzed the projected fields (PFs) of ICMS-evoked sensations - their location and spatial extent - from reports obtained over multiple years from three participants implanted with microelectrode arrays in S1. First, we found that PFs vary widely in their size across electrodes, are highly stable within electrode, are distributed over large swaths of each participant's hand, and increase in size as the amplitude or frequency of ICMS increases. Second, while PF locations match the locations of the receptive fields (RFs) of the neurons near the stimulating electrode, PFs tend to be subsumed by the corresponding RFs. Third, multi-channel stimulation gives rise to a PF that reflects the conjunction of the PFs of the component channels. By stimulating through electrodes with largely overlapping PFs, then, we can evoke a sensation that is experienced primarily at the intersection of the component PFs. To assess the functional consequence of this phenomenon, we implemented multichannel ICMS-based feedback in a bionic hand and demonstrated that the resulting sensations are more localizable than are those evoked via single-channel ICMS.

Long-term upper-extremity prosthetic control using regenerative peripheral nerve interfaces and implanted EMG electrodes

Objective.Extracting signals directly from the motor system poses challenges in obtaining both high amplitude and sustainable signals for upper-limb neuroprosthetic control. To translate neural interfaces into the clinical space, these interfaces must provide consistent signals and prosthetic performance.Approach.Previously, we have demonstrated that the Regenerative Peripheral Nerve Interface (RPNI) is a biologically stable, bioamplifier of efferent motor action potentials. Here, we assessed the signal reliability from electrodes surgically implanted in RPNIs and residual innervated muscles in humans for long-term prosthetic control.Main results.RPNI signal quality, measured as signal-to-noise ratio, remained greater than 15 for up to 276 and 1054 d in participant 1 (P1), and participant 2 (P2), respectively. Electromyography from both RPNIs and residual muscles was used to decode finger and grasp movements. Though signal amplitude varied between sessions, P2 maintained real-time prosthetic performance above 94% accuracy for 604 d without recalibration. Additionally, P2 completed a real-world multi-sequence coffee task with 99% accuracy for 611 d without recalibration.Significance.This study demonstrates the potential of RPNIs and implanted EMG electrodes as a long-term interface for enhanced prosthetic control.

Restoration of sensory information via bionic hands

Individuals who have lost the use of their hands because of amputation or spinal cord injury can use prosthetic hands to restore their independence. A dexterous prosthesis requires the acquisition of control signals that drive the movements of the robotic hand, and the transmission of sensory signals to convey information to the user about the consequences of these movements. In this Review, we describe non-invasive and invasive technologies for conveying artificial sensory feedback through bionic hands, and evaluate the technologies' long-term prospects.

Design and control of intelligent bionic artificial hand based on image recognition

BACKGROUND

At present, the popular control method for intelligent bionic prosthetic hands is EMG control. However, the control accuracy of this method is low. It is a trend to integrate computer vision into the prosthetic hand.

OBJECTIVE

The purpose of this paper is to design an intelligent prosthetic hand based on image recognition, improve the control accuracy and the quality of life of the disabled.

METHODS

Convolutional neural network is used to recognize the object to be grasped, and the recognition result is used as a trigger signal to control our intelligent prosthetic hand. We have designed a four-bar linkage mechanism and a side swing mechanism in the structure, which can not only achieve the flexion and extension of fingers but also realize the adduction and abduction of the four fingers and the lateral swing of the thumb.

RESULTS

Through the method of image recognition, the new intelligent bionic hand can achieve five kinds of Human action. Including grasp, side pinch, three-finger pinch, two-finger pinch, and pinch between fingers.

CONCLUSIONS

The experiment result proves that the precision of image recognition control is very excellent, the intelligent prosthetic hand can be completed the corresponding task.

Neuroprosthetics: from sensorimotor to cognitive disorders

Neuroprosthetics is a multidisciplinary field at the interface between neurosciences and biomedical engineering, which aims at replacing or modulating parts of the nervous system that get disrupted in neurological disorders or after injury. Although neuroprostheses have steadily evolved over the past 60 years in the field of sensory and motor disorders, their application to higher-order cognitive functions is still at a relatively preliminary stage. Nevertheless, a recent series of proof-of-concept studies suggest that electrical neuromodulation strategies might also be useful in alleviating some cognitive and memory deficits, in particular in the context of dementia. Here, we review the evolution of neuroprosthetics from sensorimotor to cognitive disorders, highlighting important common principles such as the need for neuroprosthetic systems that enable multisite bidirectional interactions with the nervous system.

Implantable intracortical microelectrodes: reviewing the present with a focus on the future

Implantable intracortical microelectrodes can record a neuron's rapidly changing action potentials (spikes). In vivo neural activity recording methods often have either high temporal or spatial resolution, but not both. There is an increasing need to record more neurons over a longer duration in vivo. However, there remain many challenges to overcome before achieving long-term, stable, high-quality recordings and realizing comprehensive, accurate brain activity analysis. Based on the vision of an idealized implantable microelectrode device, the performance requirements for microelectrodes are divided into four aspects, including recording quality, recording stability, recording throughput, and multifunctionality, which are presented in order of importance. The challenges and current possible solutions for implantable microelectrodes are given from the perspective of each aspect. The current developments in microelectrode technology are analyzed and summarized.

Detection and discrimination of electrical stimuli from an upper limb cuff electrode inM. Mulatta

Objective.Peripheral nerve interfaces seek to restore nervous system function through electrical stimulation of peripheral nerves. In clinical use, these devices should function reliably for years or decades. In this study, we assessed evoked sensations from multi-channel cuff electrode stimulation in macaque monkeys up to 711 d post-implantation.Approach.Three trained macaque monkeys received multi-channel cuff electrode implants at the median or ulnar nerves in the upper arm. Electrical stimuli from the cuff interfaces evoked sensations, which we measured via standard psychophysical tasks. We adjusted pulse amplitude or pulse width for each block with various electrode channel configurations to examine the effects of stimulus parameterization on sensation. We measured detection thresholds and just-noticeable differences (JNDs) at irregular, near-daily intervals for several months using Bayesian inferencing from trial data. We examined data trends using classical models such as Weber's Law and the strength-duration relationship using linear regression.Main results.Detection thresholds were similar between blocks with pulse width modulation and blocks with pulse amplitude modulation when represented as charge per pulse, the product of the amplitude and the pulse width. Conversely, Weber fractions-calculated as the slope of the regression between JND charge values and reference stimulus charge-were significantly different between pulse width and pulse amplitude modulation blocks for the discrimination task.Significance.Weber fractions were lower in blocks with amplitude modulation than in blocks with pulse width modulation, suggesting that pulse amplitude modulation allows finer resolution of sensory encoding above threshold. Consequently, amplitude modulation may enable a greater dynamic range for sensory perception with neuroprosthetic devices.

Artificial referred sensation in upper and lower limb prosthesis users: a systematic review

Objective.Electrical stimulation can induce sensation in the phantom limb of individuals with amputation. It is difficult to generalize existing findings as there are many approaches to delivering stimulation and to assessing the characteristics and benefits of sensation. Therefore, the goal of this systematic review was to explore the stimulation parameters that effectively elicited referred sensation, the qualities of elicited sensation, and how the utility of referred sensation was assessed.Approach.We searched PubMed, Web of Science, and Engineering Village through January of 2022 to identify relevant papers. We included papers which electrically induced referred sensation in individuals with limb loss and excluded papers that did not contain stimulation parameters or outcome measures pertaining to stimulation. We extracted information on participant demographics, stimulation approaches, and participant outcomes.Main results.After applying exclusion criteria, 49 papers were included covering nine stimulation methods. Amplitude was the most commonly adjusted parameter (n= 25), followed by frequency (n= 22), and pulse width (n= 15). Of the 63 reports of sensation quality, most reported feelings of pressure (n= 52), paresthesia (n= 48), or vibration (n= 40) while less than half (n= 29) reported a sense of position or movement. Most papers evaluated the functional benefits of sensation (n= 33) using force matching or object identification tasks, while fewer papers quantified subjective measures (n= 16) such as pain or embodiment. Only 15 studies (36%) observed percept intensity, quality, or location over multiple sessions.Significance.Most studies that measured functional performance demonstrated some benefit to providing participants with sensory feedback. However, few studies could experimentally manipulate sensation location or quality. Direct comparisons between studies were limited by variability in methodologies and outcome measures. As such, we offer recommendations to aid in more standardized reporting for future research.

Feasibility of Implanting a Foot–Ankle Endoprosthesis within Skin in a Rabbit Model of Transtibial Amputation

Prosthetic limbs that are completely implanted within skin (i.e., endoprostheses) could permit direct, physical muscle–prosthesis attachment to restore more natural sensorimotor function to people with amputation. The objective of our study was to test, in a rabbit model, the feasibility of replacing the lost foot after hindlimb transtibial amputation by implanting a novel rigid foot–ankle endoprosthesis that is fully covered with skin. We first conducted a pilot, non-survival surgery in two rabbits to determine the maximum size of the skin flap that could be made from the biological foot–ankle. The skin flap size was used to determine the dimensions of the endoprosthesis foot segment. Rigid foot–ankle endoprosthesis prototypes were successfully implanted in three rabbits. The skin incisions healed over a period of approximately 1 month after surgery, with extensive fur regrowth by the pre-defined study endpoint of approximately 2 months post surgery. Upon gross inspection, the skin surrounding the endoprosthesis appeared normal, but a substantial subdermal fibrous capsule had formed around the endoprosthesis. Histology indicated that the structure and thickness of the skin layers (epidermis and dermis) were similar between the operated and non-operated limbs. A layer of subdermal connective tissue representing the fibrous capsule surrounded the endoprosthesis. In the operated limb of one rabbit, the subdermal connective tissue layer was approximately twice as thick as the skin on the medial (skin = 0.43 mm, subdermal = 0.84 mm), ventral (skin = 0.80 mm, subdermal = 1.47 mm), and lateral (skin = 0.76 mm, subdermal = 1.42 mm) aspects of the endoprosthesis. Our results successfully demonstrated the feasibility of implanting a fully skin-covered rigid foot–ankle endoprosthesis to replace the lost tibia–foot segment of the lower limb. Concerns include the fibrotic capsule which could limit the range of motion of jointed endoprostheses. Future studies include testing of endoprosthetics, as well as materials and pharmacologic agents that may suppress fibrous encapsulation.

A finite element model of the mechanical interactions between peripheral nerves and intrafascicular implants

Objective.Intrafascicular peripheral nerve implants are key components in the development of bidirectional neuroprostheses such as touch-enabled bionic limbs for amputees. However, the durability of such interfaces is hindered by the immune response following the implantation. Among the causes linked to such reaction, the mechanical mismatch between host nerve and implant is thought to play a decisive role, especially in chronic settings.Approach.Here we focus on modeling mechanical stresses induced on the peripheral nerve by the implant's micromotion using finite element analysis. Through multiple parametric sweeps, we analyze the role of the implant's material, geometry (aspect-ratio and shape), and surface coating, deriving a set of parameters for the design of better-integrated implants.Main results.Our results indicate that peripheral nerve implants should be designed and manufactured with smooth edges, using materials at most three orders of magnitude stiffer than the nerve, and with innovative geometries to redistribute micromotion-associated loads to less delicate parts of the nerve such as the epineurium.Significance.Overall, our model is a useful tool for the peripheral nerve implant designer that is mindful of the importance of implant mechanics for long term applications.

Explainable Deep Learning Model for EMG-Based Finger Angle Estimation Using Attention

Electromyography (EMG) is one of the most common methods to detect muscle activities and intentions. However, it has been difficult to estimate accurate hand motions represented by the finger joint angles using EMG signals. We propose an encoder-decoder network with an attention mechanism, an explainable deep learning model that estimates 14 finger joint angles from forearm EMG signals. This study demonstrates that the model trained by the single-finger motion data can be generalized to estimate complex motions of random fingers. The color map result of the after-training attention matrix shows that the proposed attention algorithm enables the model to learn the nonlinear relationship between the EMG signals and the finger joint angles, which is explainable. The highly activated entries in the color map of the attention matrix derived from model training are consistent with the experimental observations in which certain EMG sensors are highly activated when a particular finger moves. In summary, this study proposes an explainable deep learning model that estimates finger joint angles based on EMG signals of the forearm using the attention mechanism.

Electro-prosthetic E-skin Successfully Delivers Elbow Joint Angle Information by Electro-prosthetic Proprioception (EPP)

Neurotraumas and neurological diseases often result in compromised proprioceptive feedback, which plays a critical role in motor control by delivering real-time position information. Electro-prosthetic proprioception (EPP) using frequency-modulated electrotactile feedback is a promising solution, as it can deliver proprioceptive information such as a joint angle via tactile channel. Prior works demonstrated that EPP successfully delivered distance information between the end effector and the target object. In this study, we implemented the electronic skin (E-skin) monitoring the elbow joint angle and delivering it to the nervous system via tactile channel. We also demonstrated that EPP improved both accuracy and precision of the elbow joint angle control. The gyroscope measuring the elbow joint angle and electrodes delivering electrotactile feedback were integrated together as a skin using thin silicon coating and polyurethane film. We call this novel E-skin, monitoring and delivering joint angle information, as an electro-prosthetic E-skin. Elbow joint angle matching test with two healthy human subjects showed that the EPP, via electro-prosthetic E-skin, enhanced 101.7% accuracy and 63.8% precision in elbow joint angle control. Clinical Relevance-Presented electro-prosthetic E-skin will address the compromised proprioceptive feedback by delivering joint angle information by electro-prosthetic proprioception (EPP) via tactile channel. This novel E-skin will open up a new path to assist and rehabilitative motor control problems after neurotraumas and neurological diseases.

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.

Extra-neural signals from severed nerves enable intrinsic hand movements in transhumeral amputations

Robotic prostheses controlled by myoelectric signals can restore limited but important hand function in individuals with upper limb amputation. The lack of individual finger control highlights the yet insurmountable gap to fully replacing a biological hand. Implanted electrodes around severed nerves have been used to elicit sensations perceived as arising from the missing limb, but using such extra-neural electrodes to record motor signals that allow for the decoding of phantom movements has remained elusive. Here, we showed the feasibility of using signals from non-penetrating neural electrodes to decode intrinsic hand and finger movements in individuals with above-elbow amputations. We found that information recorded with extra-neural electrodes alone was enough to decode phantom hand and individual finger movements, and as expected, the addition of myoelectric signals reduced classification errors both in offline and in real-time decoding.

Sensory substitution of elbow proprioception to improve myoelectric control of upper limb prosthesis: experiment on healthy subjects and amputees

BACKGROUND

Current myoelectric prostheses lack proprioceptive information and rely on vision for their control. Sensory substitution is increasingly developed with non-invasive vibrotactile or electrotactile feedback, but most systems are designed for grasping or object discriminations, and few were tested for online control in amputees. The objective of this work was evaluate the effect of a novel vibrotactile feedback on the accuracy of myoelectric control of a virtual elbow by healthy subjects and participants with an upper-limb amputation at humeral level.

METHODS

Sixteen, healthy participants and 7 transhumeral amputees performed myoelectric control of a virtual arm under different feedback conditions: vision alone (VIS), vibration alone (VIB), vision plus vibration (VIS + VIB), or no feedback at all (NO). Reach accuracy was evaluated by angular errors during discrete as well as back and forth movements. Healthy participants' workloads were assessed with the NASA-TLX questionnaire, and feedback conditions were ranked according to preference at the end of the experiment.

RESULTS

Reach errors were higher in NO than in VIB, indicating that our vibrotactile feedback improved performance as compared to no feedback. Conditions VIS and VIS+VIB display similar levels of performance and produced lower errors than in VIB. Vision remains therefore critical to maintain good performance, which is not ameliorated nor deteriorated by the addition of vibrotactile feedback. The workload associated with VIB was higher than for VIS and VIS+VIB, which did not differ from each other. 62.5% of healthy subjects preferred the VIS+VIB condition, and ranked VIS and VIB second and third, respectively.

CONCLUSION

Our novel vibrotactile feedback improved myoelectric control of a virtual elbow as compared to no feedback. Although vision remained critical, the addition of vibrotactile feedback did not improve nor deteriorate the control and was preferred by participants. Longer training should improve performances with VIB alone and reduce the need of vision for close-loop prosthesis control.

Remote Sensing System for Motor Nerve Impulse

In this article, we present our research achievements regarding the development of a remote sensing system for motor pulse acquisition, as a first step towards a complete neuroprosthetic arm. We present the fabrication process of an implantable electrode for nerve impulse acquisition, together with an innovative wirelessly controlled system. In our study, these were combined into an implantable device for attachment to peripheral nerves. Mechanical and biocompatibility tests were performed, as well as in vivo testing on pigs using the developed system. This testing and the experimental results are presented in a comprehensive manner, demonstrating that the system is capable of accomplishing the requirements of its designed application. Most significantly, neural electrical signals were acquired and transmitted out of the body during animal experiments, which were conducted according to ethical regulations in the field.

Spinal cord bioelectronic interfaces: opportunities in neural recording and clinical challenges

Bioelectronic stimulation of the spinal cord has demonstrated significant progress in restoration of motor function in spinal cord injury (SCI). The proximal, uninjured spinal cord presents a viable target for the recording and generation of control signals to drive targeted stimulation. Signals have been directly recorded from the spinal cord in behaving animals and correlated with limb kinematics. Advances in flexible materials, electrode impedance and signal analysis will allow SCR to be used in next-generation neuroprosthetics. In this review, we summarize the technological advances enabling progress in SCR and describe systematically the clinical challenges facing spinal cord bioelectronic interfaces and potential solutions, from device manufacture, surgical implantation to chronic effects of foreign body reaction and stress-strain mismatches between electrodes and neural tissue. Finally, we establish our vision of bi-directional closed-loop spinal cord bioelectronic bypass interfaces that enable the communication of disrupted sensory signals and restoration of motor function in SCI.

Evaluation of multiple perceptual qualities of transcutaneous electrical nerve stimulation for evoked tactile sensation in forearm amputees

OBJECTIVE

Evoked tactile sensation (ETS) elicited by transcutaneous electrical nerve stimulation (TENS) is promising to convey digit-specific sensory information to amputees naturally and non-invasively. Fitting ETS-based sensory feedback to amputees entails customizing coding of multiple sensory information for each stimulation site. This study was to elucidate the consistency of percepts and qualities by TENS at multiple stimulation sites in amputees retaining ETS.

APPROACH

Five transradial amputees with ETS and fourteen able-bodied subjects participated in this study. Surface electrodes with small size (10 mm in diameter) were adopted to fit the restricted projected finger map on the forearm stump of amputees. Effects of stimulus frequency on sensory types were assessed, and the map of perceptual threshold for each sensation was characterized. Sensitivity for vibration and buzz sensations was measured using distinguishable difference in stimulus pulse width. Rapid assessments for modulation ranges of pulse width at fixed amplitude and frequency were developed for coding sensory information. Buzz sensation was demonstrated for location discrimination relating to prosthetic fingers.

MAIN RESULTS

Vibration and buzz sensations were consistently evoked at 20 Hz and 50 Hz as dominant sensation types in all amputees and able-bodied subjects. Perceptual thresholds of different sensations followed a similar strength-duration curve relating stimulus amplitude to pulse width. The averaged distinguishable difference in pulse width was 12.84 ± 7.23 μs for vibration and 15.21 ± 6.47 μs for buzz in able-bodied subjects, and 14.91 ± 10.54 μs for vibration and 11.30 ± 3.42 μs for buzz in amputees. Buzz coding strategy enabled five amputees to discriminate contact of individual fingers with an overall accuracy of 77.85%.

SIGNIFICANCE

The consistency in perceptual qualities of dominant sensations can be exploited for coding multi-modality sensory feedback. A fast protocol of sensory coding is possible for fitting ETS-based, non-invasive sensory feedback to amputees.

Artificial Intelligence Enables Real-Time and Intuitive Control of Prostheses via Nerve Interface

OBJECTIVE

The next generation prosthetic hand that moves and feels like a real hand requires a robust neural interconnection between the human minds and machines.

METHODS

Here we present a neuroprosthetic system to demonstrate that principle by employing an artificial intelligence (AI) agent to translate the amputees movement intent through a peripheral nerve interface. The AI agent is designed based on the recurrent neural network (RNN) and could simultaneously decode six degree-of-freedom (DOF) from multichannel nerve data in real-time. The decoder's performance is characterized in motor decoding experiments with three human amputees.

RESULTS

First, we show the AI agent enables amputees to intuitively control a prosthetic hand with individual finger and wrist movements up to 97-98% accuracy. Second, we demonstrate the AI agent's real-time performance by measuring the reaction time and information throughput in a hand gesture matching task. Third, we investigate the AI agent's long-term uses and show the decoder's robust predictive performance over a 16-month implant duration. Conclusion & significance: Our study demonstrates the potential of AI-enabled nerve technology, underling the next generation of dexterous and intuitive prosthetic hands.

Sensory Feedback for Upper-Limb Prostheses: Opportunities and Barriers

The addition of sensory feedback to upper-limb prostheses has been shown to improve control, increase embodiment, and reduce phantom limb pain. However, most commercial prostheses do not incorporate sensory feedback due to several factors. This paper focuses on the major challenges of a lack of deep understanding of user needs, the unavailability of tailored, realistic outcome measures and the segregation between research on control and sensory feedback. The use of methods such as the Person-Based Approach and co-creation can improve the design and testing process. Stronger collaboration between researchers can integrate different prostheses research areas to accelerate the translation process.

Palatal Electrotactile Display Outperforms Visual Display in Tongue Motor learning

Incomplete tongue motor control is a common yet challenging issue among individuals with neurotraumas and neurological disorders. In development of the training protocols, multiple sensory modalities including visual, auditory, and tactile feedback have been employed. However, the effectiveness of each sensory modality in tongue motor learning is still in question. The object of this study was to test the effectiveness of visual and electrotactile assistance on tongue motor learning, respectively. Eight healthy subjects performed the tongue pointing task, in which they were visually instructed to touch the target on the palate by their tongue tip as accurately as possible. Each subject wore a custom-made dental retainer with 12 electrodes distributed over the palatal area. For visual training, 3×4 LED array on the computer screen, corresponding to the electrode layout, was turned on with different colors according to the tongue contact. For electrotactile training, electrical stimulation was applied to the tongue with frequencies depending on the distance between the tongue contact and the target, along with a small protrusion on the retainer as an indicator of the target. One baseline session, one training session, and three post-training sessions were conducted over four-day duration. Experimental result showed that the error was decreased after both visual and electrotactile trainings, from 3.56±0.11 (Mean±STE) to 1.27±0.16, and from 3.97±0.11 to 0.53±0.19, respectively. The result also showed that electrotactile training leads to stronger retention than visual training, as the improvement was retained as 62.68±1.81% after electrotactile training and 36.59±2.24% after visual training, at 3-day post training.

A Psychometric Platform to Collect Somatosensory Sensations for Neuroprosthetic Use

Somatosensory neuroprostheses exploit invasive and non-invasive feedback technologies to restore sensorimotor functions lost to disease or trauma. These devices use electrical stimulation to communicate sensory information to the brain. A sensation characterization procedure is thus necessary to determine the appropriate stimulation parameters and to establish a clear personalized map of the sensations that can be restored. Several questionnaires have been described in the literature to collect the quality, type, location, and intensity of the evoked sensations, but there is still no standard psychometric platform. Here, we propose a new psychometric system containing previously validated questionnaires on evoked sensations, which can be applied to any kind of somatosensory neuroprosthesis. The platform collects stimulation parameters used to elicit sensations and records subjects' percepts in terms of sensation location, type, quality, perceptual threshold, and intensity. It further collects data using standardized assessment questionnaires and scales, performs measurements over time, and collects phantom limb pain syndrome data. The psychometric platform is user-friendly and provides clinicians with all the information needed to assess the sensory feedback. The psychometric platform was validated with three trans-radial amputees. The platform was used to assess intraneural sensory feedback provided through implanted peripheral nerve interfaces. The proposed platform could act as a new standardized assessment toolbox to homogenize the reporting of results obtained with different technologies in the field of somatosensory neuroprosthetics.

Object Recognition via Evoked Sensory Feedback during Control of a Prosthetic Hand

Haptic and proprioceptive feedback is critical for sensorimotor integration when we use our hand to perform daily tasks. Here, we evaluated how externally evoked haptic and proprioceptive feedback and myoelectric control strategies affected the recognition of object properties when participants controlled a prosthetic hand. Fingertip haptic sensation was elicited using a transcutaneous nerve stimulation grid to encode the prosthetic's fingertip forces. An array of tactors elicited patterned vibratory stimuli to encode tactile-proprioceptive kinematic information of the prosthetic finger joint. Myoelectric signals of the finger flexor and extensor were used to control the position or velocity of joint angles of the prosthesis. Participants were asked to perform object property (stiffness and size) recognition, by controlling the prosthetic hand with concurrent haptic and tactile-proprioceptive feedback. With the evoked feedback, intact and amputee participants recognized the object stiffness and size at success rates ranging from 50% to 100% in both position and velocity control with no significant difference across control schemes. Our findings show that evoked somatosensory feedback in a non-invasive manner can facilitate closed-loop control of the prosthetic hand and allowed for simultaneous recognition of different object properties. The outcomes can facilitate our understanding on the role of sensory feedback during bidirectional human-machine interactions, which can potentially promote user experience in object interactions using prosthetic hands.

In Vivo Cellular-Level 3D Imaging of Peripheral Nerves Using a Dual-Focusing Technique for Intra-Neural Interface Implantation

In vivo volumetric imaging of the microstructural changes of peripheral nerves with an inserted electrode could be key for solving the chronic implantation failure of an intra-neural interface necessary to provide amputated patients with natural motion and sensation. Thus far, no imaging devices can provide a cellular-level three-dimensional (3D) structural images of a peripheral nerve in vivo. In this study, an optical coherence tomography-based peripheral nerve imaging platform that employs a newly proposed depth of focus extension technique is reported. A point spread function with the finest transverse resolution of 1.27 µm enables the cellular-level volumetric visualization of the metal wire and microstructural changes in a rat sciatic nerve with the metal wire inserted in vivo. Further, the feasibility of applying the imaging platform to large animals for a preclinical study is confirmed through in vivo rabbit sciatic nerve imaging. It is expected that new possibilities for the successful chronic implantation of an intra-neural interface will open up by providing the 3D microstructural changes of nerves around the inserted electrode.

Modeling optical design parameters for fine stimulation in sciatic nerve of optogenetic mice

Optogenetics presents an alternative method for interfacing with the nervous system over the gold-standard of electrical stimulation. While electrical stimulation requires electrodes to be surgically embedded in tissue for in vivo studies, optical stimulation offers a less-invasive approach that may yield more specific, localized stimulation. The advent of optogenetic laboratory animals-whose motor neurons can be activated when illuminated with blue light-enables research into refining optical stimulation of the mammalian nervous system where subsets of nerve fibers within a nerve may be stimulated without embedding any device directly into the nerve itself. However, optical stimulation has a major drawback in that light is readily scattered and absorbed in tissue thereby limiting the depth with which a single emission source can penetrate. We hypothesize that the use of multiple, focused light emissions deployed around the circumference of a nerve can overcome these light-scattering limitations. To understand the physical parameters necessary to produce pinpointed light stimulation within a single nerve, we employed a simplified Monte Carlo simulation to estimate the size of nerves where this technique may be successful, as well as the necessary optical lens design for emitters to be used during future in vivo studies. By modeling multiple focused beams, we find that only fascicles within a nerve diameter less than 1 mm are fully accessible to focused optical stimulation; a minimum of 4 light sources is required to generate a photon intensity at a point in a nerve over the initial contact along its surface. To elicit the same effect in larger nerves, focusing lenses would require a numerical aperture [Formula: see text]. These simulations inform on the design of instrumentation capable of stimulating disparate motor neurons in mouse sciatic nerve to control hindlimb movement.

A Bionic Hand for Semi-Autonomous Fragile Object Manipulation via Proximity and Pressure Sensors

Multiarticulate bionic hands are now capable of recreating the endogenous movements and grip patterns of the human hand, yet amputees continue to be dissatisfied with existing control strategies. One approach towards more dexterous and intuitive control is to create a semi-autonomous bionic hand that can synergistically aid a human with complex tasks. To that end, we have developed a bionic hand that can automatically detect and grasp nearby objects with minimal force using multi-modal fingertip sensors. We evaluated performance using a fragile-object task in which participants must move an object over a barrier without applying pressure above specified thresholds. Participants completed the task under three conditions: 1) with their native hand, 2) with the bionic hand using surface electromyography control, and 3) using the semi-autonomous bionic hand. We show that the semi-autonomous hand is extremely capable of completing this dexterous task and significantly outperforms a more traditional surface-electromyography controller. Furthermore, we show that the semi-autonomous bionic hand significantly increased users' grip precision and reduced users' perceived task workload. This work constitutes an important step towards more dexterous and intuitive bionic hands and serves as a foundation for future work on shared human-machine control for intelligent bionic systems.

Neurorobotic fusion of prosthetic touch, kinesthesia, and movement in bionic upper limbs promotes intrinsic brain behaviors

[Figure: see text].

Solving musculoskeletal biomechanics with machine learning

Deep learning is a relatively new computational technique for the description of the musculoskeletal dynamics. The experimental relationships of muscle geometry in different postures are the high-dimensional spatial transformations that can be approximated by relatively simple functions, which opens the opportunity for machine learning (ML) applications. In this study, we challenged general ML algorithms with the problem of approximating the posture-dependent moment arm and muscle length relationships of the human arm and hand muscles. We used two types of algorithms, light gradient boosting machine (LGB) and fully connected artificial neural network (ANN) solving the wrapping kinematics of 33 muscles spanning up to six degrees of freedom (DOF) each for the arm and hand model with 18 DOFs. The input-output training and testing datasets, where joint angles were the input and the muscle length and moment arms were the output, were generated by our previous phenomenological model based on the autogenerated polynomial structures. Both models achieved a similar level of errors: ANN model errors were 0.08 ± 0.05% for muscle lengths and 0.53 ± 0.29% for moment arms, and LGB model made similar errors-0.18 ± 0.06% and 0.13 ± 0.07%, respectively. LGB model reached the training goal with only 103 samples, while ANN required 106 samples; however, LGB models were about 39 times slower than ANN models in the evaluation. The sufficient performance of developed models demonstrates the future applicability of ML for musculoskeletal transformations in a variety of applications, such as in advanced powered prosthetics.

Physiologic signaling and viability of the muscle cuff regenerative peripheral nerve interface (MC-RPNI) for intact peripheral nerves

Background. Robotic exoskeleton devices have become a promising modality for restoration of extremity function in individuals with limb loss or functional weakness. However, there exists no consistent or reliable way to record efferent motor action potentials from intact peripheral nerves to control device movement. Peripheral nerve motor action potentials are similar in amplitude to that of background noise, producing an unfavorable signal-to-noise ratio (SNR) that makes these signals difficult to detect and interpret. To address this issue, we have developed the muscle cuff regenerative peripheral nerve interface (MC-RPNI), a construct consisting of a free skeletal muscle graft wrapped circumferentially around an intact peripheral nerve. Over time, the muscle graft regenerates, and the intact nerve undergoes collateral axonal sprouting to reinnervate the muscle. The MC-RPNI amplifies efferent motor action potentials by several magnitudes, thereby increasing the SNR, allowing for higher fidelity signaling and detection of motor intention. The goal of this study was to characterize the signaling capabilities and viability of the MC-RPNI over time.Methods. Thirty-seven rats were randomly assigned to one of five experimental groups (Groups A-E). For MC-RPNI animals, their contralateral extensor digitorum longus (EDL) muscle was harvested and trimmed to either 8 mm (Group A) or 13 mm (Group B) in length, wrapped circumferentially around the intact ipsilateral common peroneal (CP) nerve, secured, and allowed to heal for 3 months. Additionally, one 8 mm (Group C) and one 13 mm (Group D) length group had an epineurial window created in the CP nerve immediately preceding MC-RPNI creation. Group E consisted of sham surgery animals. At 3 months, electrophysiologic analyses were conducted to determine the signaling capabilities of the MC-RPNI. Additionally, electromyography and isometric force analyses were performed on the CP-innervated EDL to determine the effects of the MC-RPNI on end organ function. Following evaluation, the CP nerve, MC-RPNI, and ipsilateral EDL muscle were harvested for histomorphometric analysis.Results. Study endpoint analysis was performed at 3 months post-surgery. All rats displayed visible muscle contractions in both the MC-RPNI and EDL following proximal CP nerve stimulation. Compound muscle action potentials were recorded from the MC-RPNI following proximal CP nerve stimulation and ranged from 3.67 ± 0.58 mV to 6.04 ± 1.01 mV, providing efferent motor action potential amplification of 10-20 times that of a normal physiologic nerve action potential. Maximum tetanic isometric force (F_o) testing of the distally-innervated EDL muscle in MC-RPNI groups producedF_o(2341 ± 114 mN-2832 ± 102 mN) similar to controls (2497 ± 122 mN), thus demonstrating that creation of MC-RPNIs did not adversely impact the function of the distally-innervated EDL muscle. Overall, comparison between all MC-RPNI sub-groups did not reveal any statistically significant differences in signaling capabilities or negative effects on distal-innervated muscle function as compared to the control group.Conclusions. MC-RPNIs have the capability to provide efferent motor action potential amplification from intact nerves without adversely impacting distal muscle function. Neither the size of the muscle graft nor the presence of an epineurial window in the nerve had any significant impact on the ability of the MC-RPNI to amplify efferent motor action potentials from intact nerves. These results support the potential for the MC-RPNI to serve as a biologic nerve interface to control advanced exoskeleton devices.