Neural interfaces for somatosensory feedback: bringing life to a prosthesis

Selective intrafascicular stimulation of myelinated and unmyelinated nerve fibers through a longitudinal electrode: A computational study

Carbon nanotube (CNT) fiber electrodes have demonstrated exceptional spatial selectivity and sustained reliability in the context of intrafascicular electrical stimulation, as evidenced through rigorous animal experimentation. A significant presence of unmyelinated C fibers, known to induce uncomfortable somatosensory experiences, exists within peripheral nerves. This presence poses a considerable challenge to the excitation of myelinated Aβ fibers, which are crucial for tactile sensation. To achieve nuanced tactile sensory feedback utilizing CNT fiber electrodes, the selective stimulation of Aβ sensory afferents emerges as a critical factor. In confronting this challenge, the present investigation sought to refine and apply a rat sciatic-nerve model leveraging the capabilities of the COMSOL-NEURON framework. This approach enables a systematic evaluation of the influence exerted by stimulation parameters and electrode geometry on the activation dynamics of both myelinated Aβ and unmyelinated C fibers. The findings advocate for the utilization of current pulses featuring a pulse width of 600 μs, alongside the deployment of CNT fibers characterized by a diminutive diameter of 10 μm, with an exclusively exposed cross-sectional area, to facilitate reduced activation current thresholds. Comparative analysis under monopolar and bipolar electrical stimulation conditions revealed proximate activation thresholds, albeit with bipolar stimulation exhibiting superior fiber selectivity relative to its monopolar counterpart. Concerning pulse waveform characteristics, the adoption of an anodic-first biphasic stimulation modality is favored, taking into account the dual criteria of activation threshold and fiber selectivity optimization. Consequently, this investigation furnishes an efficacious stimulation paradigm for the selective activation of touch-related nerve fibers, alongside provisioning a comprehensive theoretical foundation for the realization of natural tactile feedback within the domain of prosthetic hand applications.

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.

An Artificial Olfactory System Based on a Chemi-Memristive Device

Technologies based on the fusion of gas sensors and neuromorphic computing to mimic the olfactory system have immense potential. However, the implementation of neuromorphic olfactory systems remains in a state of infancy because conventional gas sensors lack the necessary functions. Therefore, this study proposes a hysteretic "chemi-memristive gas sensor" based on oxygen vacancy chemi-memristive dynamics that differ from that of conventional gas sensors. After the memristive switching operation, the redox reaction with the external gas molecules is enhanced, resulting in the generation and elimination of oxygen vacancies that induce rapid current changes. In addition, the pre-generated oxygen vacancies enhance the post-sensing properties. Therefore, fast responses, short recovery times, and hysteretic gas response are achieved by the proposed sensor at room temperature. Based on the advantageous functionality of the sensor, device-level olfactory systems that can monitor the history of input gas stimuli are experimentally demonstrated as a potential application. Moreover, analog conductance modulation induced by oxidizing and reducing gases enables the conversion of external gas stimuli into synaptic weights and hence the realization of typical synaptic functionalities without an additional device or circuit. The proposed chemi-memristive device represents an advance in the bioinspired technology adopted in creating artificial intelligence systems.

Encoding force modulation in two electrotactile feedback parameters strengthens sensory integration according to maximum likelihood estimation

Bidirectional human-machine interfaces involve commands from the central nervous system to an external device and feedback characterizing device state. Such feedback may be elicited by electrical stimulation of somatosensory nerves, where a task-relevant variable is encoded in stimulation amplitude or frequency. Recently, concurrent modulation in amplitude and frequency (multimodal encoding) was proposed. We hypothesized that feedback with multimodal encoding may effectively be processed by the central nervous system as two independent inputs encoded in amplitude and frequency, respectively, thereby increasing state estimate quality in accordance with maximum-likelihood estimation. Using an adaptation paradigm, we tested this hypothesis during a grasp force matching task where subjects received electrotactile feedback encoding instantaneous force in amplitude, frequency, or both, in addition to their natural force feedback. The results showed that adaptations in grasp force with multimodal encoding could be accurately predicted as the integration of three independent inputs according to maximum-likelihood estimation: amplitude modulated electrotactile feedback, frequency modulated electrotactile feedback, and natural force feedback (r² = 0.73). These findings show that multimodal electrotactile feedback carries an intrinsic advantage for state estimation accuracy with respect to single-variable modulation and suggest that this scheme should be the preferred strategy for bidirectional human-machine interfaces with electrotactile feedback.

Microstimulation of sensory cortex engages natural sensory representations

Cortical activity patterns occupy a small subset of possible network states. If this is due to intrinsic network properties, microstimulation of sensory cortex should evoke activity patterns resembling those observed during natural sensory input. Here, we use optical microstimulation of virally transfected layer 2/3 pyramidal neurons in the mouse primary vibrissal somatosensory cortex to compare artificially evoked activity with natural activity evoked by whisker touch and movement ("whisking"). We find that photostimulation engages touch- but not whisking-responsive neurons more than expected by chance. Neurons that respond to photostimulation and touch or to touch alone exhibit higher spontaneous pairwise correlations than purely photoresponsive neurons. Exposure to several days of simultaneous touch and optogenetic stimulation raises both overlap and spontaneous activity correlations among touch and photoresponsive neurons. We thus find that cortical microstimulation engages existing cortical representations and that repeated co-presentation of natural and artificial stimulation enhances this effect.

Toward higher-performance bionic limbs for wider clinical use

Most prosthetic limbs can autonomously move with dexterity, yet they are not perceived by the user as belonging to their own body. Robotic limbs can convey information about the environment with higher precision than biological limbs, but their actual performance is substantially limited by current technologies for the interfacing of the robotic devices with the body and for transferring motor and sensory information bidirectionally between the prosthesis and the user. In this Perspective, we argue that direct skeletal attachment of bionic devices via osseointegration, the amplification of neural signals by targeted muscle innervation, improved prosthesis control via implanted muscle sensors and advanced algorithms, and the provision of sensory feedback by means of electrodes implanted in peripheral nerves, should all be leveraged towards the creation of a new generation of high-performance bionic limbs. These technologies have been clinically tested in humans, and alongside mechanical redesigns and adequate rehabilitation training should facilitate the wider clinical use of bionic limbs.

Restoring After Central Nervous System Injuries: Neural Mechanisms and Translational Applications of Motor Recovery

Central nervous system (CNS) injuries, including stroke, traumatic brain injury, and spinal cord injury, are leading causes of long-term disability. It is estimated that more than half of the survivors of severe unilateral injury are unable to use the denervated limb. Previous studies have focused on neuroprotective interventions in the affected hemisphere to limit brain lesions and neurorepair measures to promote recovery. However, the ability to increase plasticity in the injured brain is restricted and difficult to improve. Therefore, over several decades, researchers have been prompted to enhance the compensation by the unaffected hemisphere. Animal experiments have revealed that regrowth of ipsilateral descending fibers from the unaffected hemisphere to denervated motor neurons plays a significant role in the restoration of motor function. In addition, several clinical treatments have been designed to restore ipsilateral motor control, including brain stimulation, nerve transfer surgery, and brain–computer interface systems. Here, we comprehensively review the neural mechanisms as well as translational applications of ipsilateral motor control upon rehabilitation after CNS injuries.

Peripheral neurostimulation for encoding artificial somatosensations

The direct neural stimulation of peripheral or central nervous systems has been shown as an effective tool to treat neurological conditions. The electrical activation of the nervous sensory pathway can be adopted to restore the artificial sense of touch and proprioception in people suffering from sensory-motor disorders. The modulation of the neural stimulation parameters has a direct effect on the electrically induced sensations, both when targeting the somatosensory cortex and the peripheral somatic nerves. The properties of the artificial sensations perceived, as their location, quality and intensity are strongly dependent on the direct modulation of pulse width, amplitude and frequency of the neural stimulation. Different sensory encoding schemes have been tested in patients showing distinct effects and outcomes according to their impact on the neural activation. Here, I reported the most adopted neural stimulation strategies to artificially encode somatosensation into the peripheral nervous system. The real-time implementation of these strategies in bionic devices is crucial to exploit the artificial sensory feedback in prosthetics. Thus, neural stimulation becomes a tool to directly communicate with the human nervous system. Given the importance of adding artificial sensory information to neuroprosthetic devices to improve their control and functionality, the choice of an optimal neural stimulation paradigm could increase the impact of prosthetic devices on the quality of life of people with sensorimotor disabilities.

Local Environment Induces Differential Gene Expression in Regenerating Nerves

INTRODUCTION

Approximately 80% of amputations are complicated by neuromas. Methods for neuroma management include nerve translocation into bone and implantation into skeletal muscle grafts, which have also facilitated the development of regenerative neural interfaces to enable fixation of prosthetics with motor and sensory feedback. However, molecular-level differences between nerves in these environments have not been investigated. This study aimed to elucidate the physiology of regenerating nerves in different settings by assessing gene expression.

MATERIALS AND METHODS

New Zealand white rabbits underwent transfemoral amputation with sciatic nerve transposition into the femur or tacked to skeletal muscle. At 5 wk, ribonucleic acid (RNA) sequencing of samples of distal nerve terminating in bone or muscle and nerve of the contralateral limb (control) identified differentially expressed genes (DEGs) and biochemical pathways (α = 0.05).

RESULTS

Three samples of nerve housed in bone, four of nerve tacked to muscle, and seven naïve controls were analyzed. Relative to controls, nerve housed in bone had little within-group variation and 13,028 DEGs, and nerve tacked to muscle had dramatic within-group variation and 12,811 DEGs. These samples upregulated the following pathways: lysosome, phagosome, antigen processing/presentation, and cell adhesion molecule. Relative to nerve housed in bone, nerve tacked to muscle had 12,526 DEGs, demonstrating upregulation of pathways of B-cell receptor signaling, focal adhesion, natural killer-cell mediated cytotoxicity, leukocyte transendothelial migration, and extracellular matrix-receptor interactions.

CONCLUSIONS

Nerve housed in bone has a more predictable molecular profile than does nerve tacked to muscle. Thus, the intramedullary canal may provide a more reliable setting for neuroma prevention and neural interfacing.

Bidirectional bionic limbs: a perspective bridging technology and physiology

Precise control of bionic limbs relies on robust decoding of motor commands from nerves or muscles signals and sensory feedback from artificial limbs to the nervous system by interfacing the afferent nerve pathways. Implantable devices for bidirectional communication with bionic limbs have been developed in parallel with research on physiological alterations caused by an amputation. In this perspective article, we question whether increasing our effort on bridging these technologies with a deeper understanding of amputation pathophysiology and human motor control may help to overcome pressing stalls in the next generation of bionic limbs.

Sensory Substitution for Tactile Feedback in Upper Limb Prostheses

Present commercially available prosthetic devices fall short when it comes to providing users with accurate and non-invasive tactile feedback from their artificial limb, leading to more difficult control and leaving many at a heightened risk of device rejection. Current methods of simulating hand sensation in patients affected by upper limb loss are either invasive and expensive, or otherwise sub-optimal in their feedback mechanism. Here we propose, build, and implement a novel device for tactile feedback in upper limb prostheses. The device consists of an adaptable tactile sensing glove that can be applied to existing artificial limbs and an audio feedback system that leverages the plasticity of the brain to communicate touch to the user through sensory substitution. This device aims to take advantage of the existing pathways between auditory and tactile sensory regions in the brain by mapping force magnitude and location from the integrated force sensors on the gloves to specific volume and frequency, respectively. The device was successfully manufactured for proof of concept, and further testing with prosthetic users will aim to assess the efficacy of the device and identify potential modifications for use in research and commercialization.

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

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

Static and dynamic proprioceptive recognition through vibrotactile stimulation

Objective.Proprioceptive information provides individuals with a sense of our limb's static position and dynamic movement. Impaired or a lack of such feedback can diminish our ability to perform dexterous motions with our biological limbs or assistive devices. Here we seek to determine whether both static and dynamic components of proprioception can be recognized using variation of the spatial and temporal components of vibrotactile feedback.Approach.An array of five vibrotactors was placed on the forearm of each subject. Each tactor was encoded to represent one of the five forearm postures. Vibratory stimulus was elicited to convey the static position and movement of the forearm. Four experimental blocks were performed to test each subject's recognition of a forearm's simulated static position, rotational amplitude, rotational amplitude and direction, and rotational speed.Main results.Our results showed that the subjects were able to perform proprioceptive recognition based on the delivered vibrotactile information. Specifically, rotational amplitude recognition resulted in the highest level of accuracy (99.0%), while the recognition accuracy of the static position and the rotational amplitude-direction was the lowest (91.7% and 90.8%, respectively). Nevertheless, all proprioceptive properties were perceived with >90% accuracy, indicating that the implemented vibrotactile encoding scheme could effectively provide proprioceptive information to the users.Significance.The outcomes suggest that information pertaining to static and dynamic aspects of proprioception can be accurately delivered using an array of vibrotactors. This feedback approach could be used to potentially evaluate the sensorimotor integration processes during human-machine interactions, and to improve sensory feedback in clinical populations with somatosensory impairments.

Treatment Recommendations for Phantom Limb Pain in People with Amputations: An Expert Consensus Delphi Study

Background

Phantom limb pain (PLP) is common and often accompanied by serious suffering. Current systematic‐review evidence suggests that recommended treatments are no more effective than placebo for reducing PLP. Given the difficulty in conducting a meta‐analysis for nonpharmacological treatments and the weak evidence for pharmacological treatments for PLP, consensus on the first‐line management of PLP needs to be reached using alternative methods.

Objective

To reach expert consensus and make recommendations on the effective management of PLP.

Design

A three‐round Delphi design was used.

Setting

The study was conducted using e‐mail and Google survey tool as the main methods of communication and providing feedback.

Participants

The study included 27 clinicians and researchers from various health disciplines who are experts in PLP management.

Method

Data were collected using three sequential rounds of anonymous online questionnaires where experts proposed and ranked the treatments for PLP. A consensus was reached on the treatments that were endorsed by 50% or more of the experts.

Results

Thirty‐seven treatments were proposed for the management of PLP at the beginning of the study. Consensus was reached on seven treatments that were considered effective for managing PLP and on two treatments that were considered ineffective. Graded motor imagery, mirror therapy, amitriptyline, sensory discrimination training, and use of a functional prosthesis were endorsed by most experts because of the available backing scientific evidence and their reported efficacy in clinical practice. Cognitive behavioral therapy and virtual reality training were endorsed by most experts because of their reported efficacy in clinical practice despite indicating a dearth of scientific evidence to support their ranking. Citalopram and dorsal root ganglion pulsed radiofrequency were rejected owing to a lack of relevant scientific evidence.

Conclusion

The results of this study suggest that the nonpharmacological treatments endorsed in this study may have an important role in the management of PLP.

Embodied cognition: So flexible as to be "disembodied"?

This review aims to explore what I call the "Embodiment Cost Hypothesis" (ECH), according to which, when humans "embody" a part of the world other than their bodies, a measurable cost is detectable on their real bodies. The review analyzes experimental evidence in favor of the ECH by examining studies from different research fields, including studies of action observation (2), tool-use (3), rubber hand illusion (4), and full-body illusions (5). In light of this literature, this review argues that embodiment effects can profitably be seen as phenomena associated with both benefits (resulting from the embodiment of external objects/bodies) and costs (resulting from the disembodiment at various levels of the subject's own body). Implications are discussed in relation to the ongoing debate on the embodied cognition (EC) approach.

Emerging Frontier of Peripheral Nerve and Organ Interfaces

The development of new tools to interface with the nervous system, empowered by advances in electronics and materials science, has transformed neuroscience and is informing therapies for neurological and mental conditions. Although the vast majority of neural engineering research has focused on advancing tools to study the brain, understanding the peripheral nervous system and other organs can similarly benefit from these technologies. To realize this vision, the neural interface technologies need to address the biophysical, mechanical, and chemical challenges posed by the peripheral nerves and organs. In this Perspective, we discuss design considerations and recent technological advances to modulate electrical signaling outside the central nervous system. The innovations in bioelectronics borne out of interdisciplinary collaborations between biologists and physical scientists may not only advance fundamental study of peripheral (neuro)physiology but also empower clinical interventions for conditions including neurological, gastrointestinal, and immune dysfunction.

Recent Developments in Prosthesis Sensors, Texture Recognition, and Sensory Stimulation for Upper Limb Prostheses

Current developments being made in upper limb prostheses are focused on replacing lost sensory information to the amputees. Providing sensory stimulation from the prosthesis can directly improve control over the prosthetic and provide a sense of body ownership. The focus of this review article is on recent developments while including foundational knowledge for some of the critical concepts in neural prostheses. Reported concepts follow the flow of information from sensors to signal processing, with emphasis on texture recognition, and then to sensory stimulation strategies that reestablish the lost sensory feedback loop. Prosthetic sensors are used to detect the physical environment, converting pressure, force, and position into electrical signals. The electrical signals can then be processed in an effort to identify the surrounding environment using distinctive characteristics such as stiffness and texture. In order for the amputee to use this information in a natural manner, there must be real-time sensory stimulation, perception, and motor control of the prosthesis. Although truly complete sensory replacement has not yet been realized, some basic percepts can be partially restored, allowing progress towards a more realistic prosthesis with natural sensations.

Brain reactions to the use of sensorized hand prosthesis in amputees

OBJECTIVE

We investigated for the first time the presence of chronic changes in the functional organization of sensorimotor brain areas induced by prolonged training with a bidirectional hand prosthesis.

METHODS

A multimodal neurophysiological and neuroimaging evaluation of brain functional changes occurring during training in five consecutive amputees participating to experimental trials with robotic hands over a period of 10 years was carried out. In particular, modifications to the functional anatomy of sensorimotor brain areas under resting conditions were explored in order to check for eventual changes with respect to baseline.

RESULTS

Full evidence is provided to demonstrate brain functional changes, and some of them in both the hemispheres and others restricted to the hemisphere contralateral to the amputation/prosthetic hand.

CONCLUSIONS

The study describes a unique experimental experience showing that brain reactions to the prolonged use of an artificial hand can be tracked for a tailored approach to a fully embedded artificial upper limb for future chronic uses in daily activities.

Computational challenges and opportunities for a bi-directional artificial retina

A future artificial retina that can restore high acuity vision in blind people will rely on the capability to both read (observe) and write (control) the spiking activity of neurons using an adaptive, bi-directional and high-resolution device. Although current research is focused on overcoming the technical challenges of building and implanting such a device, exploiting its capabilities to achieve more acute visual perception will also require substantial computational advances. Using high-density large-scale recording and stimulation in the primate retina with an ex vivo multi-electrode array lab prototype, we frame several of the major computational problems, and describe current progress and future opportunities in solving them. First, we identify cell types and locations from spontaneous activity in the blind retina, and then efficiently estimate their visual response properties by using a low-dimensional manifold of inter-retina variability learned from a large experimental dataset. Second, we estimate retinal responses to a large collection of relevant electrical stimuli by passing current patterns through an electrode array, spike sorting the resulting recordings and using the results to develop a model of evoked responses. Third, we reproduce the desired responses for a given visual target by temporally dithering a diverse collection of electrical stimuli within the integration time of the visual system. Together, these novel approaches may substantially enhance artificial vision in a next-generation device.

Stiffness Perception using Transcutaneous Electrical Stimulation during Active and Passive Prosthetic Control

Haptic feedback allows an individual to identify various object properties. In this preliminary study, we determined the performance of stiffness recognition using transcutaneous nerve stimulation when a prosthetic hand was moved passively or was controlled actively by the subjects. Using a 2x8 electrode grid placed along the subject's upper arm, electrical stimulation was delivered to evoke somatotopic sensation along their index finger. Stimulation intensity, i.e. sensation strength, was modulated using the fingertip forces from a sensorized prosthetic hand. Object stiffness was encoded based on the rate of change of the evoked sensation as the prosthesis grasped one of three objects of different stiffness levels. During active control, sensation was modulated in real time as recorded forces were converted to stimulation amplitudes. During passive control, prerecorded force traces were randomly selected from a pool. Our results showed that the accuracy of object stiffness recognition was similar in both active and passive conditions. A slightly lower accuracy was observed during active control in one subject, which indicated that the sensorimotor integration processes could affect haptic perception for some users.

Evoking haptic sensations in the foot through high-density transcutaneous electrical nerve stimulations

OBJECTIVE

Evoking haptic sensation on upper limb amputees via peripheral nerve stimulation has been investigated intensively in the past decade, but related studies involving lower limb amputees are limited. This study aimed to evaluate the feasibility of using non-invasive transcutaneous electrical nerve stimulation to evoke haptic sensation along the phantom limb of the amputated foot of transtibial amputees.

APPROACH

A high-density electrode grid (4 × 4) was placed over the skin surface above the distal branching of the sciatic, tibial, and common peroneal nerves. We hypothesized that electrical stimulation delivered to distinct electrode pairs created unique electric fields, which can activate selective sets of sensory axons innervating different skin regions of the foot. Five transtibial amputee subjects (three unilateral and two bilateral) and one able-bodied subject were tested by scanning all possible electrode pair combinations.

MAIN RESULTS

All subjects reported various haptic percepts at distinct regions along the foot with each corresponding to specific electrode pairs. These results demonstrated the capability of our non-invasive nerve stimulation method to evoke haptic sensations in the foot of transtibial amputees and the able-bodied subject.

SIGNIFICANCE

The outcomes contribute important knowledge and evidence regarding missing tactile sensation in the foot of lower limb amputees and might also facilitate future development of strategies to manage phantom pain and enhance embodiment of prosthetic legs in the future.

Is an artificial limb embodied as a hand? Brain decoding in prosthetic limb users

The potential ability of the human brain to represent an artificial limb as a body part (embodiment) has been inspiring engineers, clinicians, and scientists as a means to optimise human-machine interfaces. Using functional MRI (fMRI), we studied whether neural embodiment actually occurs in prosthesis users' occipitotemporal cortex (OTC). Compared with controls, different prostheses types were visually represented more similarly to each other, relative to hands and tools, indicating the emergence of a dissociated prosthesis categorisation. Greater daily life prosthesis usage correlated positively with greater prosthesis categorisation. Moreover, when comparing prosthesis users' representation of their own prosthesis to controls' representation of a similar looking prosthesis, prosthesis users represented their own prosthesis more dissimilarly to hands, challenging current views of visual prosthesis embodiment. Our results reveal a use-dependent neural correlate for wearable technology adoption, demonstrating adaptive use-related plasticity within the OTC. Because these neural correlates were independent of the prostheses' appearance and control, our findings offer new opportunities for prosthesis design by lifting restrictions imposed by the embodiment theory for artificial limbs.

Modelling the effects of ephaptic coupling on selectivity and response patterns during artificial stimulation of peripheral nerves

Artificial electrical stimulation of peripheral nerves for sensory feedback restoration can greatly benefit from computational models for simulation-based neural implant design in order to reduce the trial-and-error approach usually taken, thus potentially significantly reducing research and development costs and time. To this end, we built a computational model of a peripheral nerve trunk in which the interstitial space between the fibers and the tissues was modelled using a resistor network, thus enabling distance-dependent ephaptic coupling between myelinated axons and between fascicles as well. We used the model to simulate a) the stimulation of a nerve trunk model with a cuff electrode, and b) the propagation of action potentials along the axons. Results were used to investigate the effect of ephaptic interactions on recruitment and selectivity stemming from artificial (i.e., neural implant) stimulation and on the relative timing between action potentials during propagation. Ephaptic coupling was found to increase the number of fibers that are activated by artificial stimulation, thus reducing the artificial currents required for axonal recruitment, and it was found to reduce and shift the range of optimal stimulation amplitudes for maximum inter-fascicular selectivity. During propagation, while fibers of similar diameters tended to lock their action potentials and reduce their conduction velocities, as expected from previous knowledge on bundles of identical axons, the presence of many other fibers of different diameters was found to make their interactions weaker and unstable.

Object Shape and Surface Topology Recognition Using Tactile Feedback Evoked through Transcutaneous Nerve Stimulation

Tactile feedback is critical for distinguishing different object properties. In this article, we determined if tactile feedback evoked by transcutaneous nerve stimulation can be used to detect objects of different shape and surface topology. To evoke tactile sensation at different fingers, a 2x8 electrode grid was placed along the subject's upper arm, and two concurrent electrical stimulation trains targeted the median and ulnar nerve bundles, which evoked individually modulated sensations at different fingers. Fingertip forces of the prosthetic hand were transformed to stimulation current amplitude. Object shape was encoded based on finger-object contact timing. Surface topology represented by ridge height and spacing was encoded through current amplitude and stimulation time interval, respectively. The elicited sensation allowed subjects to determine object shape with success rates >84%. Surface topology recognition resulted in success rates >81%. Our findings suggest that tactile feedback evoked from transcutaneous nerve stimulation allows the recognition of object shape and surface topology. The ability to recognize these properties may help improve object manipulation and promote fine control of a prosthetic hand.

Neural Implants Without Electronics: A Proof-of-Concept Study on a Human Skin Model

Objective: Chronic neural implants require energy and signal supply. The objective of this work was to evaluate a multichannel transcutaneous coupling approach in an ex vivo split-concept study, which minimizes the invasiveness of such an implant by externalizing the processing electronics. Methods: Herein, the experimental work focused on the transcutaneous energy and signal transmission. The performance was discussed with widely evaluated concepts of neural interfaces in the literature. Results: The performance of the transcutaneous coupling approach increased with higher channel count and higher electrode pitches. Electrical crosstalk among channels was present, but acceptable for the stimulation of peripheral nerves. Conclusions: Transcutaneous coupling with extracorporeal transmitting arrays and subcutaneous counterparts provide a promising alternative to the inductive concept particularly when a fully integration of the system in a prosthetic shaft is intended. The relocation of the electronics can potentially prevent pressure sores, improve accessibility for maintenance and increase lifetime of the implant.

Object stiffness recognition using haptic feedback delivered through transcutaneous proximal nerve stimulation

OBJECTIVE

Haptic feedback is crucial when we manipulate objects. Information pertaining to an object's stiffness in particular can help facilitate fine motor control. In this study, we seek to determine whether objects of different stiffness levels can be recognized using haptic feedback provided by transcutaneous electrical stimulation of peripheral nerves.

APPROACH

Using a stimulation electrode grid placed along the medial side of the upper arm, the median and ulnar nerve bundles were targeted to evoke haptic sensation on the palmar side of the hand. Stimulation current amplitude was modulated in real-time with the fingertip force recorded from a sensorized prosthetic hand. In order to evaluate which stimulation pattern was more critical, object stiffness was encoded either by the rate of change of the stimulus amplitude or the level of peak stimulus amplitude, as the prosthesis grasped the objects.

MAIN RESULTS

Both encoding methods allowed the subjects to differentiate objects of different stiffness levels with  >90% accuracy. No significant difference was observed between the two encoding methods, which indicated that both the rate of change of the stimulation amplitude and the peak stimulation amplitude could effectively provide stiffness information of the objects.

SIGNIFICANCE

The outcomes suggest that it is possible to elicit haptic sensations describing various object stiffness levels using transcutaneous nerve stimulation. The haptic feedback associated with object stiffness can facilitate object manipulation/interactions. It may also improve user experience during human-machine interactions, when object stiffness information is incorporated.

Hybrid LAE-CMOS Force-Sensing System Employing TFT-Based Compressed Sensing for Scalability of Tactile Sensing Skins

Tactile sensing requires form-fitting and dense sensor arrays over large-areas. Hybrid systems, combining Large-Area Electronics (LAE) and silicon-CMOS ICs to respectively provide diverse sensing and high-performance computation/control, enable a platform for such sensing. A key challenge is that hybrid systems require a large number of interfaces between the LAE and CMOS domains, particularly as the number of sensors scales. This paper presents an architecture that exploits the attribute of signal sparsity, commonly exhibited in large-scale tactile-sensing applications, to reduce the interfacing complexity to a level set by the sparsity rather than the number of sensors. This enhances scalability compared to sequential-scanning and active-matrix approaches. The architecture implements compressed sensing via thin-film-transistor (TFT) switches, and is demonstrated in a force-sensing system with 20 force sensors, a TFT die (with 161 ZnO TFTs) per sensor, and a custom CMOS IC for system readout and control. Acquisition error of 0.7 k[Formula: see text] is achieved over a 100 k Ω-20 k Ω sensing range, at energy and rate of 2.46  μ J/frame and 31 fps.

Bionic reconstruction : Restoration of extremity function with osseointegrated and mind-controlled prostheses

Background

Loss of an extremity at any level has a major impact on a patient’s life. Using bionic reconstruction, extremity function can be restored and the patient reintegrated into daily life. Surgical procedures including selective nerve transfer and anchoring of prostheses into bone are combined with structured rehabilitation and modern prosthetic fitting. The patient is thereby able to use the prostheses intuitively and with multiple degrees of freedom.

Methods

This article presents the concept and approach for modern bionic reconstruction in detail and the relevant literature. The nerve transfer matrices for targeted muscle reinnervation (TMR) and the concept of osseointegration to optimally fit a patient with a modern prosthesis are described in detail. As a clinical example, the case of a patient who suffered from traumatic amputation and subsequently received TMR in combination with an osseointegrated implant and structured rehabilitation is presented.

Results

Using bionic reconstruction, basic hand functions can be restored and bimanual dexterity can expand the range of daily activities. Besides this approach to bionic reconstruction, its advantages and disadvantages are compared to hand transplantation. The limitations and perspectives of modern bionic reconstruction are also discussed.

Conclusions

Bionic reconstruction is a sophisticated method for restoring extremity function and nowadays can be considered a standard of care for all levels of upper extremity amputations. An interdisciplinary approach and structured rehabilitation are necessary to master prosthetic function to ultimately reintegrate patients into daily life.

Perceptions of Self of Persons with Visible Artificial Devices : A Review of the Literature

Not much is known about the self-perceptions of persons using prosthetic devices. The purpose of the literature review was to explore the self-perceptions of persons living with visible artificial devices from published articles between 2010 and 2017. Using key words to search for published literature in the PubMed,CINAHL, IEEE Proceedings, and Scopus indices showed 680 articles. Braun and Clarke's six phases of qualitative thematic analysis were used on 25 articles meeting the inclusion criteria, revealing 29 data extracts (themes) as data summaries. Three key thematic categories were revealed : Body image and ownership, integration of prosthetic device into the self-body, and suspended enjoyment or delight, reflecting the longings for completeness affecting persons' use of prosthetic devices. Consistent with self-perceptions understood through social biases and customs, completeness is achieved through the happy paradox of a person made whole through artificial devices. This experience informs nursing practice in helping people find meaning in their life. Further research into selfperceptions with prosthetic devices is essential, particularly those reflecting the cultural influences of artificial devices on quality of life. J.Med.Invest. 66:58-64, February, 2019.

Soft Conducting Elastomer for Peripheral Nerve Interface

State-of-the-art intraneural electrodes made from silicon or polyimide substrates have shown promise in selectively modulating efferent and afferent activity in the peripheral nervous system. However, when chronically implanted, these devices trigger a multiphase foreign body response ending in device encapsulation. The presence of encapsulation increases the distance between the electrode and the excitable tissue, which not only reduces the recordable signal amplitude but also requires increased current to activate nearby axons. Herein, this study reports a novel conducting polymer based intraneural electrode which has Young's moduli similar to that of nerve tissue. The study first describes material optimization of the soft wire conductive matrix and evaluates their mechanical and electrochemical properties. Second, the study demonstrates 3T3 cell survival when cultured with media eluted from the soft wires. Third, the study presents acute in vivo functionality for stimulation of peripheral nerves to evoke force and compound muscle action potential in a rat model. Furthermore, comprehensive histological analyses show that soft wires elicit significantly less scar tissue encapsulation, less changes to axon size, density and morphology, and reduced macrophage activation compared to polyimide implants in the sciatic nerves at 1 month postimplantation.

Towards neural co-processors for the brain: combining decoding and encoding in brain-computer interfaces

The field of brain-computer interfaces is poised to advance from the traditional goal of controlling prosthetic devices using brain signals to combining neural decoding and encoding within a single neuroprosthetic device. Such a device acts as a 'co-processor' for the brain, with applications ranging from inducing Hebbian plasticity for rehabilitation after brain injury to reanimating paralyzed limbs and enhancing memory. We review recent progress in simultaneous decoding and encoding for closed-loop control and plasticity induction. To address the challenge of multi-channel decoding and encoding, we introduce a unifying framework for developing brain co-processors based on artificial neural networks and deep learning. These 'neural co-processors' can be used to jointly optimize cost functions with the nervous system to achieve desired behaviors ranging from targeted neuro-rehabilitation to augmentation of brain function.

Neural Networks for Modeling Neural Spiking in S1 Cortex

Somatosensation is composed of two distinct modalities: touch, arising from sensors in the skin, and proprioception, resulting primarily from sensors in the muscles, combined with these same cutaneous sensors. In contrast to the wealth of information about touch, we know quite less about the nature of the signals giving rise to proprioception at the cortical level. Likewise, while there is considerable interest in developing encoding models of touch-related neurons for application to brain machine interfaces, much less emphasis has been placed on an analogous proprioceptive interface. Here we investigate the use of Artificial Neural Networks (ANNs) to model the relationship between the firing rates of single neurons in area 2, a largely proprioceptive region of somatosensory cortex (S1) and several types of kinematic variables related to arm movement. To gain a better understanding of how these kinematic variables interact to create the proprioceptive responses recorded in our datasets, we train ANNs under different conditions, each involving a different set of input and output variables. We explore the kinematic variables that provide the best network performance, and find that the addition of information about joint angles and/or muscle lengths significantly improves the prediction of neural firing rates. Our results thus provide new insight regarding the complex representations of the limb motion in S1: that the firing rates of neurons in area 2 may be more closely related to the activity of peripheral sensors than it is to extrinsic hand position. In addition, we conduct numerical experiments to determine the sensitivity of ANN models to various choices of training design and hyper-parameters. Our results provide a baseline and new tools for future research that utilizes machine learning to better describe and understand the activity of neurons in S1.

Evoked Haptic Sensation in the Hand With Concurrent Non-Invasive Nerve Stimulation

OBJECTIVE

Haptic perception is critical for prosthetic users to control their prosthetic hand intuitively. In this study, we seek to evaluate the haptic perception evoked from concurrent stimulation trains through multiple channels using transcutaneous nerve stimulation.

METHODS

A 2 × 8 electrode grid was used to deliver current to the median and ulnar nerves in the upper arm. Different electrodes were first selected to activate the sensory axons, which can elicit sensations at different locations of the hand. Charge-balanced bipolar stimulation was then delivered to two sets of electrodes concurrently with a phase delay (dual stimulation) to determine whether the evoked sensation can be constructed from sensations of single stimulation delivered separately at different locations (single stimulation) along the electrode grid. The temporal delay between the two stimulation trains was altered to evaluate potential interference. The short-term stability of the haptic sensation within a testing session was also evaluated.

RESULTS

The evoked sensation during dual stimulation was largely a direct summation of the sensation from single stimulations. The delay between the two stimulation locations had minimal effect on the evoked sensations, which was also stable over repeated testing within a session.

CONCLUSION

Our results indicated that the haptic sensations at different regions of the hand can be constructed by combining the response from multiple stimulation trains directly. The interference between stimulations were minimal.

SIGNIFICANCE

The outcomes will allow us to construct specific haptic sensation patterns when the prosthesis interacts with different objects, which may help improve user embodiment of the prosthesis.

Targeted muscle reinnervation and prosthetic rehabilitation after limb loss

Over one million amputations occur annually world-wide. Often, amputation of the neoplastic limb is regarded as a surgical failure and the end of surgical care for the patient. Here, we highlight the advancements in extremity prostheses and surgical techniques that should change that mindset. Myoelectric prostheses, osseointegration, and targeted muscle reinnervation allow for more intuitive and easy to use devices, reduced pain, and greater quality of life for amputees.

Merged Haptic Sensation in the Hand during Concurrent Non-Invasive Proximal Nerve Stimulation

When individuals interact with the environment, sensory feedback is a critical aspect of the experience. Individuals using prosthesis often have difficulty controlling their device, partly due to a lack of sensory information. Transcutaneous nerve stimulation has the potential to elicit focal haptic sensation when controlled electrical current was delivered to a pair of electrodes in proximity to the nerve. The objective of this preliminary study was to evaluate how different elicited focal haptic sensation were altered, when multiple concurrent electrical stimuli were delivered to different portions of the median and ulnar nerve bundles. The delay between the individual stimulation during concurrent stimuli was also varied to identify if this parameter could alter the resulting sensation region. Lastly, the stability/repeatability of the perceived sensation during concurrent stimuli was determined. Our preliminary results showed that the spatial distribution of the haptic sensation was largely a direct summation/merge of the sensation regions from the individual nerve stimulation when comparing the regions to that of the concurrent double stimulation. Our results also showed that merged sensation region was not sensitive to different time delays the two concurrent stimuli. Lastly, the sensation regions remained stable and showed repeatable sensation in the hand even with 20-60 minutes between repeated stimulations.

Leg Prosthesis With Somatosensory Feedback Reduces Phantom Limb Pain and Increases Functionality

Phantom limb pain (PLP) develops in most patients with lower limb amputation. Changes in the peripheral and central nervous system (CNS) are hypothesized to contribute to PLP. Based on ideas to modify neural reorganization within the CNS, the aim of the study was to test, whether prostheses with somatosensory feedback might help to reduce PLP, and increase the functionality of movement with a prosthesis. We therefore equipped the prostheses of 14 lower leg amputees with a simple to use feedback system that provides electrocutaneous feedback to patients' thigh whenever the foot and toes of the prosthesis touch the ground. Two weeks of training with such a feedback prosthesis reduced PLP, increased the functional use of the prosthesis, and increased patients' satisfaction with prosthesis use. We found a significant overall reduction of PLP during the course of the training period. Most patients reported lower PLP intensities at the end of the day while before training they have usually experienced maximal PLP intensities. Furthermore, patients also reported larger walking distances and more stable walking and better posture control while walking on and across a bumpy or soft ground. After training, the majority of participants (9/14) preferred such a feedback system over no feedback. This study extends former observations of a similar training procedure with arm amputees who used a similar feedback training to improve the functionality of an arm prosthesis in manipulating and grasping objects.

Assessing the quality of supplementary sensory feedback using the crossmodal congruency task

Advanced neural interfaces show promise in making prosthetic limbs more biomimetic and ultimately more intuitive and useful for patients. However, approaches to assess these emerging technologies are limited in scope and the insight they provide. When outfitting a prosthesis with a feedback system, such as a peripheral nerve interface, it would be helpful to quantify its physiological correspondence, i.e. how well the prosthesis feedback mimics the perceived feedback in an intact limb. Here we present an approach to quantify this aspect of feedback quality using the crossmodal congruency effect (CCE) task. We show that CCE scores are sensitive to feedback modality, an important characteristic for assessment purposes, but are confounded by the spatial separation between the expected and perceived location of a stimulus. Using data collected from 60 able-bodied participants trained to control a bypass prosthesis, we present a model that results in adjusted-CCE scores that are unaffected by percept misalignment which may result from imprecise neural stimulation. The adjusted-CCE score serves as a proxy for a feedback modality's physiological correspondence or 'naturalness'. This quantification approach gives researchers a tool to assess an aspect of emerging augmented feedback systems that is not measurable with current motor assessments.