The science and engineering behind sensitized brain-controlled bionic hands.

Advances in our understanding of brain function, along with the development of neural interfaces that allow for the monitoring and activation of neurons, have paved the way for brain-machine interfaces (BMIs), which harness neural signals to reanimate the limbs via electrical activation of the muscles or to control extracorporeal devices, thereby bypassing the muscles and senses altogether. BMIs consist of reading out motor intent from the neuronal responses monitored in motor regions of the brain and executing intended movements with bionic limbs, reanimated limbs, or exoskeletons. BMIs also allow for the restoration of the sense of touch by electrically activating neurons in somatosensory regions of the brain, thereby evoking vivid tactile sensations and conveying feedback about object interactions. In this review, we discuss the neural mechanisms of motor control and somatosensation in able-bodied individuals and describe approaches to use neuronal responses as control signals for movement restoration and to activate residual sensory pathways to restore touch. Although the focus of the review is on intracortical approaches, we also describe alternative signal sources for control and noninvasive strategies for sensory restoration.

Assessing the manufacturable 32-channel cochlear electrode array: evaluation results for clinical trials.

Reliability evaluation results of a manufacturable 32-channel cochlear electrode array are reported in this paper. Applying automated laser micro-machining process and a layer-by-layer silicone deposition scheme, authors developed the manufacturing methods of the electrode array for fine patterning and mass production. The developed electrode array has been verified through the requirements specified by the ISO Standard 14708-7. And the insertion trauma of the electrode array has been evaluated based on human temporal bone studies. According to the specified requirements, the electrode array was assessed through elongation & insulation, flexural, and fatigue tests. In addition, Temporal bone study was performed using eight fresh-frozen cadaver temporal bones with the electrode arrays inserted via the round window. Following soaking in saline condition, the impedances between conducting wires of the electrode array were measured over 100 kΩ (the pass/fail criterion). After each required test, it was shown that the electrode array maintained the electrical continuity and insulation condition. The average insertion angle of the electrode array inside the scala tympani was 399.7°. The human temporal bone studies exhibited atraumatic insertion rate of 60.3% (grade 0 or 1). The reliability of the manufacturable electrode array is successfully verified in mechanical, electrical, and histological aspects. Following the completion of a 32-channel cochlear implant system, the performance and stability of the 32-channel electrode array will be evaluated in clinical trials.

The frequency of cortical microstimulation shapes artificial touch.

Intracortical microstimulation (ICMS) of the somatosensory cortex evokes vivid tactile sensations and can be used to convey sensory feedback from brain-controlled bionic hands. Changes in ICMS frequency lead to changes in the resulting sensation, but the discriminability of frequency has only been investigated over a narrow range of low frequencies. Furthermore, the sensory correlates of changes in ICMS frequency remain poorly understood. Specifically, it remains to be elucidated whether changes in frequency only modulate sensation magnitude-as do changes in amplitude-or whether they also modulate the quality of the sensation. To fill these gaps, we trained monkeys to discriminate the frequency of ICMS pulse trains over a wide range of frequencies (from 10 to 400 Hz). ICMS amplitude also varied across stimuli to dissociate sensation magnitude from ICMS frequency and ensure that animals could not make frequency judgments based on magnitude. We found that animals could consistently discriminate ICMS frequency up to ∼200 Hz but that the sensory correlates of frequency were highly electrode dependent: On some electrodes, changes in frequency were perceptually distinguishable from changes in amplitude-seemingly giving rise to a change in sensory quality; on others, they were not. We discuss the implications of our findings for neural coding and for brain-controlled bionic hands.

An Aqueous Electrolyte Gated Artificial Synapse with Synaptic Plasticity Selectively Mediated by Biomolecules.

The emulation of functions and behaviors of biological synapses using electronic devices has inspired the development of artificial neural networks (ANNs) in biomedical interfaces. Despite the achievements, artificial synapses that can be selectively responsive to non-electroactive biomolecules and directly operate in biological environments are still lacking. Herein, we report an artificial synapse based on organic electrochemical transistors and investigate the selective modulation of its synaptic plasticity by glucose. The enzymatic reaction between glucose and glucose oxidase results in long-term modulation of the channel conductance, mimicking selective binding of biomolecules to their receptors and consequent long-term modulation of the synaptic weight. Moreover, the device shows enhanced synaptic behaviors in the blood serum at a higher glucose concentration, which suggests its potential application in vivo as artificial neurons. This work provides a step towards the fabrication of ANNs with synaptic plasticity selectively mediated by biomolecules for neuro-prosthetics and human-machine interfaces.

Mechanical Impedance of Rat Glabrous Skin and Its Relation With Skin Morphometry.

The mechanical impedance of intact and epidermis-peeled rat glabrous skin was studied at two sites (digit and sole) and at two frequencies (40 Hz and 250 Hz). The thicknesses of skin layers at the corresponding regions were measured histologically from intact- and peeled-skin samples in every subject. Compared to intact sole skin, digital rat skin has thicker layers and higher mechanical resistance, and it is less stiff. The resistance of the skin significantly decreased after epidermal peeling at both the digit and the sole. Furthermore, peeling caused the reactance to become positive due to inertial effects. As the frequency was increased from 40 to 250 Hz, the resistance and stiffness also increased for the intact skin, while the peeled skin showed less frictional (i.e., resistance) but more inertial (i.e., positive reactance) effects. We estimated the mechanical properties of epidermis and dermis with lumped-element models developed for both intact and peeled conditions. The models predicted that dermis has higher mass, lower stiffness, and lower resistance compared to epidermis, similar to the experimental impedance results obtained in the peeled condition which consisted mostly of dermis. The overall impedance was simulated more successfully at 40 Hz. When both frequencies are considered, the models produced consistent results for resistance in both conditions. The results imply that most of the model parameters should be frequency-dependent and suggest that mechanical properties of epidermis can be related to its thickness. These findings may help in designing artificial skin for neuroprosthetic limbs.

Creating a neuroprosthesis for active tactile exploration of textures.

Intracortical microstimulation (ICMS) of the primary somatosensory cortex (S1) can produce percepts that mimic somatic sensation and, thus, has potential as an approach to sensorize prosthetic limbs. However, it is not known whether ICMS could recreate active texture exploration-the ability to infer information about object texture by using one's fingertips to scan a surface. Here, we show that ICMS of S1 can convey information about the spatial frequencies of invisible virtual gratings through a process of active tactile exploration. Two rhesus monkeys scanned pairs of visually identical screen objects with the fingertip of a hand avatar-controlled first via a joystick and later via a brain-machine interface-to find the object with denser virtual gratings. The gratings consisted of evenly spaced ridges that were signaled through individual ICMS pulses generated whenever the avatar's fingertip crossed a ridge. The monkeys learned to interpret these ICMS patterns, evoked by the interplay of their voluntary movements and the virtual textures of each object, to perform a sensory discrimination task. Discrimination accuracy followed Weber's law of just-noticeable differences (JND) across a range of grating densities; a finding that matches normal cutaneous sensation. Moreover, 1 monkey developed an active scanning strategy where avatar velocity was integrated with the ICMS pulses to interpret the texture information. We propose that this approach could equip upper-limb neuroprostheses with direct access to texture features acquired during active exploration of natural objects.

Speaker Responsibility for Synthetic Speech Derived from Neural Activity.

This article provides analysis of the mechanisms and outputs involved in language-use mediated by a neuroprosthetic device. It is motivated by the thought that users of speech neuroprostheses require sufficient control over what their devices externalize as synthetic speech if they are to be thought of as responsible for it, but that the nature of this control, and so the status of their responsibility, is not clear.

Sensing and decoding the neural drive to paralyzed muscles during attempted movements of a person with tetraplegia using a sleeve array.

Motor neurons convey information about motor intent that can be extracted and interpreted to control assistive devices. However, most methods for measuring the firing activity of single neurons rely on implanted microelectrodes. Although intracortical brain-computer interfaces (BCIs) have been shown to be safe and effective, the requirement for surgery poses a barrier to widespread use that can be mitigated by instead using noninvasive interfaces. The objective of this study was to evaluate the feasibility of deriving motor control signals from a wearable sensor that can detect residual motor unit activity in paralyzed muscles after chronic cervical spinal cord injury (SCI). Despite generating no observable hand movement, volitional recruitment of motor units below the level of injury was observed across attempted movements of individual fingers and overt wrist and elbow movements. Subgroups of motor units were coactive during flexion or extension phases of the task. Single digit movement intentions were classified offline from the electromyogram (EMG) power [root-mean-square (RMS)] or motor unit firing rates with median classification accuracies >75% in both cases. Simulated online control of a virtual hand was performed with a binary classifier to test feasibility of real-time extraction and decoding of motor units. The online decomposition algorithm extracted motor units in 1.2 ms, and the firing rates predicted the correct digit motion 88 ± 24% of the time. This study provides the first demonstration of a wearable interface for recording and decoding firing rates of motor units below the level of injury in a person with motor complete SCI.NEW & NOTEWORTHY A wearable electrode array and machine learning methods were used to record and decode myoelectric signals and motor unit firing in paralyzed muscles of a person with motor complete tetraplegia. The myoelectric activity and motor unit firing rates were task specific, even in the absence of visible motion, enabling accurate classification of attempted single-digit movements. This wearable system has the potential to enable people with tetraplegia to control assistive devices through movement intent.

Neuroprosthetics: an outlook on active challenges toward clinical adoption.

Neural prostheses are designed to counter the effects of neurotrauma and restore the fundamental building blocks of human experience including motor action, sensation, and meaningful communication with other individuals. Here, we present an overview of active avenues, open questions, and debated topics in neuroprosthetics, such as targeting the mechanisms of sensorimotor recovery and designing brain interfaces for scalability. We review leading opinions in this thriving field, aiming to inform translational practice toward clinical adoption.

Activities of daily living with bionic arm improved by combination training and latching filter in prosthesis control comparison.

BACKGROUND: Advanced prostheses can restore function and improve quality of life for individuals with amputations. Unfortunately, most commercial control strategies do not fully utilize the rich control information from residual nerves and musculature. Continuous decoders can provide more intuitive prosthesis control using multi-channel neural or electromyographic recordings. Three components influence continuous decoder performance: the data used to train the algorithm, the algorithm, and smoothing filters on the algorithm's output. Individual groups often focus on a single decoder, so very few studies compare different decoders using otherwise similar experimental conditions. METHODS: We completed a two-phase, head-to-head comparison of 12 continuous decoders using activities of daily living. In phase one, we compared two training types and a smoothing filter with three algorithms (modified Kalman filter, multi-layer perceptron, and convolutional neural network) in a clothespin relocation task. We compared training types that included only individual digit and wrist movements vs. combination movements (e.g., simultaneous grasp and wrist flexion). We also compared raw vs. nonlinearly smoothed algorithm outputs. In phase two, we compared the three algorithms in fragile egg, zipping, pouring, and folding tasks using the combination training and smoothing found beneficial in phase one. In both phases, we collected objective, performance-based (e.g., success rate), and subjective, user-focused (e.g., preference) measures. RESULTS: Phase one showed that combination training improved prosthesis control accuracy and speed, and that the nonlinear smoothing improved accuracy but generally reduced speed. Phase one importantly showed simultaneous movements were used in the task, and that the modified Kalman filter and multi-layer perceptron predicted more simultaneous movements than the convolutional neural network. In phase two, user-focused metrics favored the convolutional neural network and modified Kalman filter, whereas performance-based metrics were generally similar among all algorithms. CONCLUSIONS: These results confirm that state-of-the-art algorithms, whether linear or nonlinear in nature, functionally benefit from training on more complex data and from output smoothing. These studies will be used to select a decoder for a long-term take-home trial with implanted neuromyoelectric devices. Overall, clinical considerations may favor the mKF as it is similar in performance, faster to train, and computationally less expensive than neural networks.

Brain-computer interfaces for amyotrophic lateral sclerosis.

A brain-computer interface (BCI) is a device that detects signals from the brain and transforms them into useful commands. Researchers have developed BCIs that utilize different kinds of brain signals. These different BCI systems have differing characteristics, such as the amount of training required and the degree to which they are or are not invasive. Much of the research on BCIs to date has involved healthy individuals and evaluation of classification algorithms. Some BCIs have been shown to have potential benefit for users with minimal muscular function as a result of amyotrophic lateral sclerosis. However, there are still several challenges that need to be successfully addressed before BCIs can be clinically useful.

The future of upper extremity rehabilitation robotics: research and practice.

The loss of upper limb motor function can have a devastating effect on people's lives. To restore upper limb control and functionality, researchers and clinicians have developed interfaces to interact directly with the human body's motor system. In this invited review, we aim to provide details on the peripheral nerve interfaces and brain-machine interfaces that have been developed in the past 30 years for upper extremity control, and we highlight the challenges that still remain to transition the technology into the clinical market. The findings show that peripheral nerve interfaces and brain-machine interfaces have many similar characteristics that enable them to be concurrently developed. Decoding neural information from both interfaces may lead to novel physiological models that may one day fully restore upper limb motor function for a growing patient population.

Ownership of an artificial limb induced by electrical brain stimulation.

Replacing the function of a missing or paralyzed limb with a prosthetic device that acts and feels like one's own limb is a major goal in applied neuroscience. Recent studies in nonhuman primates have shown that motor control and sensory feedback can be achieved by connecting sensors in a robotic arm to electrodes implanted in the brain. However, it remains unknown whether electrical brain stimulation can be used to create a sense of ownership of an artificial limb. In this study on two human subjects, we show that ownership of an artificial hand can be induced via the electrical stimulation of the hand section of the somatosensory (SI) cortex in synchrony with touches applied to a rubber hand. Importantly, the illusion was not elicited when the electrical stimulation was delivered asynchronously or to a portion of the SI cortex representing a body part other than the hand, suggesting that multisensory integration according to basic spatial and temporal congruence rules is the underlying mechanism of the illusion. These findings show that the brain is capable of integrating "natural" visual input and direct cortical-somatosensory stimulation to create the multisensory perception that an artificial limb belongs to one's own body. Thus, they serve as a proof of concept that electrical brain stimulation can be used to "bypass" the peripheral nervous system to induce multisensory illusions and ownership of artificial body parts, which has important implications for patients who lack peripheral sensory input due to spinal cord or nerve lesions.

Advances in neuroprosthetic management of foot drop: a review.

This paper reviews the technological advances and clinical results obtained in the neuroprosthetic management of foot drop. Functional electrical stimulation has been widely applied owing to its corrective abilities in patients suffering from a stroke, multiple sclerosis, or spinal cord injury among other pathologies. This review aims at identifying the progress made in this area over the last two decades, addressing two main questions: What is the status of neuroprosthetic technology in terms of architecture, sensorization, and control algorithms?. What is the current evidence on its functional and clinical efficacy? The results reveal the importance of systems capable of self-adjustment and the need for closed-loop control systems to adequately modulate assistance in individual conditions. Other advanced strategies, such as combining variable and constant frequency pulses, could also play an important role in reducing fatigue and obtaining better therapeutic results. The field not only would benefit from a deeper understanding of the kinematic, kinetic and neuromuscular implications and effects of more promising assistance strategies, but also there is a clear lack of long-term clinical studies addressing the therapeutic potential of these systems. This review paper provides an overview of current system design and control architectures choices with regard to their clinical effectiveness. Shortcomings and recommendations for future directions are identified.

Brain Recording, Mind-Reading, and Neurotechnology: Ethical Issues from Consumer Devices to Brain-Based Speech Decoding.

Brain reading technologies are rapidly being developed in a number of neuroscience fields. These technologies can record, process, and decode neural signals. This has been described as 'mind reading technology' in some instances, especially in popular media. Should the public at large, be concerned about this kind of technology? Can it really read minds? Concerns about mind-reading might include the thought that, in having one's mind open to view, the possibility for free deliberation, and for self-conception, are eroded where one isn't at liberty to privately mull things over. Themes including privacy, cognitive liberty, and self-conception and expression appear to be areas of vital ethical concern. Overall, this article explores whether brain reading technologies are really mind reading technologies. If they are, ethical ways to deal with them must be developed. If they are not, researchers and technology developers need to find ways to describe them more accurately, in order to dispel unwarranted concerns and address appropriately those that are warranted.

A new methodology to record from human primary afferents provides insight for somatosensory neuroprosthetics.

Muscle spindles are integral to proprioception and their behavior is of particular interest for the design of somatosensory neuroprostheses. Prior knowledge about human muscle spindles has been limited to microneurography recordings in peripheral nerves using joint movements that do not disrupt the electrode. Recent studies demonstrate a new methodology for studying the afferent encoding of proprioception during freestanding, providing important information for neural engineering and the broader scientific community (Knellwolf TP, Burton AR, Hammam E, Macefield VG. J Neurophysiol 120: 953-959, 2018; Knellwolf TP, Burton AR, Hammam E, Macefield VG. J Neurophysiol 121: 74-84, 2019; Macefield VG, Knellwolf TP. J Neurophysiol 120: 452-467, 2018).

Calcium activation of cortical neurons by continuous electrical stimulation: Frequency dependence, temporal fidelity, and activation density.

Electrical stimulation of the brain has become a mainstay of fundamental neuroscience research and an increasingly prevalent clinical therapy. Despite decades of use in basic neuroscience research and the growing prevalence of neuromodulation therapies, gaps in knowledge regarding activation or inactivation of neural elements over time have limited its ability to adequately interpret evoked downstream responses or fine-tune stimulation parameters to focus on desired responses. In this work, in vivo two-photon microscopy was used to image neuronal calcium activity in layer 2/3 neurons of somatosensory cortex (S1) in male C57BL/6J-Tg(Thy1-GCaMP6s)GP4.3Dkim/J mice during 30 s of continuous electrical stimulation at varying frequencies. We show frequency-dependent differences in spatial and temporal somatic responses during continuous stimulation. Our results elucidate conflicting results from prior studies reporting either dense spherical activation of somas biased toward those near the electrode, or sparse activation of somas at a distance via axons near the electrode. These findings indicate that the neural element specific temporal response local to the stimulating electrode changes as a function of applied charge density and frequency. These temporal responses need to be considered to properly interpret downstream circuit responses or determining mechanisms of action in basic science experiments or clinical therapeutic applications.

Phantom limb pain: peripheral neuromodulatory and neuroprosthetic approaches to treatment.

Post-amputation phantom limb pain (PLP) is a widespread phenomenon that can have physical, psychological, and functional impacts on amputees who experience the condition. The varying presentations and mechanisms of PLP make it difficult to effectively provide long-term pain relief. Multiple neuromodulatory approaches to treating PLP have focused on electrical stimulation of the peripheral nervous system, with varying degrees of success. More recently, research has been done to study the effects of neuroprosthetic approaches on PLP. Neuroprosthetics combine the use of a functional prosthetic with stimulation to the peripheral nerves in the residual limb. Although many of the neuroprosthetic studies focus on improving function, several have shown preliminary evidence for the reduction of severity of PLP. In this review we provide an overview of the current understanding of the neurological mechanisms that initiate and sustain PLP, as well as the neuromodulatory and neuroprosthetic approaches under development for treatment of the condition. Muscle Nerve 59:154-167, 2019.

Microneurography as a tool to develop decoding algorithms for peripheral neuro-controlled hand prostheses.

BACKGROUND: The usability of dexterous hand prostheses is still hampered by the lack of natural and effective control strategies. A decoding strategy based on the processing of descending efferent neural signals recorded using peripheral neural interfaces could be a solution to such limitation. Unfortunately, this choice is still restrained by the reduced knowledge of the dynamics of human efferent signals recorded from the nerves and associated to hand movements. FINDINGS: To address this issue, in this work we acquired neural efferent activities from healthy subjects performing hand-related tasks using ultrasound-guided microneurography, a minimally invasive technique, which employs needles, inserted percutaneously, to record from nerve fibers. These signals allowed us to identify neural features correlated with force and velocity of finger movements that were used to decode motor intentions. We developed computational models, which confirmed the potential translatability of these results showing how these neural features hold in absence of feedback and when implantable intrafascicular recording, rather than microneurography, is performed. CONCLUSIONS: Our results are a proof of principle that microneurography could be used as a useful tool to assist the development of more effective hand prostheses.

Stable, three degree-of-freedom myoelectric prosthetic control via chronic bipolar intramuscular electrodes: a case study.

BACKGROUND: Modern prosthetic hands are typically controlled using skin surface electromyographic signals (EMG) from remaining muscles in the residual limb. However, surface electrode performance is limited by changes in skin impedance over time, day-to-day variations in electrode placement, and relative motion between the electrodes and underlying muscles during movement: these limitations require frequent retraining of controllers. In the presented study, we used chronically implanted intramuscular electrodes to minimize these effects and thus create a more robust prosthetic controller. METHODS: A study participant with a transradial amputation was chronically implanted with 8 intramuscular EMG electrodes. A K Nearest Neighbor (KNN) regression velocity controller was trained to predict intended joint movement direction using EMG data collected during a single training session. The resulting KNN was evaluated over 12 weeks and in multiple arm posture configurations, with the participant controlling a 3 Degree-of-Freedom (DOF) virtual reality (VR) hand to match target VR hand postures. The performance of this EMG-based controller was compared to a position-based controller that used movement measured from the participant's opposite (intact) hand. Surface EMG was also collected for signal quality comparisons. RESULTS: Signals from the implanted intramuscular electrodes exhibited less crosstalk between the various channels and had a higher Signal-to-Noise Ratio than surface electrode signals. The performance of the intramuscular EMG-based KNN controller in the VR control task showed no degradation over time, and was stable over the 6 different arm postures. Both the EMG-based KNN controller and the intact hand-based controller had 100% hand posture matching success rates, but the intact hand-based controller was slightly superior in regards to speed (trial time used) and directness of the VR hand control (path efficiency). CONCLUSIONS: Chronically implanted intramuscular electrodes provide negligible crosstalk, high SNR, and substantial VR control performance, including the ability to use a fixed controller over 12 weeks and under different arm positions. This approach can thus be a highly effective platform for advanced, multi-DOF prosthetic control.