Background and Objective. Kinematic analysis of reaching movements is increasingly used to evaluate upper extremity function after cerebrovascular insults in humans and has also been applied to rodent models. Such analyses can require time-consuming frame-by-frame inspections and are affected by the experimenter's bias. In this study, we introduce a semi-automated algorithm for tracking forepaw movements in mice. This methodology allows us to calculate several kinematic measures for the quantitative assessment of performance in a skilled reaching task before and after a focal cortical stroke. Methods. Mice were trained to reach for food pellets with their preferred paw until asymptotic performance was achieved. Photothrombosis was then applied to induce a focal ischemic injury in the motor cortex, contralateral to the trained limb. Mice were tested again once a week for 30 days. A high frame rate camera was used to record the movements of the paw, which was painted with a nontoxic dye. An algorithm was then applied off-line to track the trajectories and to compute kinematic measures for motor performance evaluation. Results. The tracking algorithm proved to be fast, accurate, and robust. A number of kinematic measures were identified as sensitive indicators of poststroke modifications. Based on end-point measures, ischemic mice appeared to improve their motor performance after 2 weeks. However, kinematic analysis revealed the persistence of specific trajectory adjustments up to 30 days poststroke, indicating the use of compensatory strategies. Conclusions. These results support the use of kinematic analysis in mice as a tool for both detection of poststroke functional impairments and tracking of motor improvements following rehabilitation. Similar studies could be performed in parallel with human studies to exploit the translational value of this skilled reaching analysis.
Neuromodulation of spinal sensorimotor circuits improves motor control in animal models and humans with spinal cord injury. With common neuromodulation devices, electrical stimulation parameters are tuned manually and remain constant during movement. We developed a mechanistic framework to optimize neuromodulation in real time to achieve high-fidelity control of leg kinematics during locomotion in rats. We first uncovered relationships between neuromodulation parameters and recruitment of distinct sensorimotor circuits, resulting in predictive adjustments of leg kinematics. Second, we established a technological platform with embedded control policies that integrated robust movement feedback and feed-forward control loops in real time. These developments allowed us to conceive a neuroprosthetic system that controlled a broad range of foot trajectories during continuous locomotion in paralyzed rats. Animals with complete spinal cord injury performed more than 1000 successive steps without failure, and were able to climb staircases of various heights and lengths with precision and fluidity. Beyond therapeutic potential, these findings provide a conceptual and technical framework to personalize neuromodulation treatments for other neurological disorders.
Researchers have succeeded in partly restoring damaged vestibular functionality in several animal models. Recently, acute interventions have also been demonstrated in human patients. Our previous work on a vestibular implant for humans used predefined stimulation patterns; here we present a research tool that facilitates motion-modulated stimulation. This requires a system that can process gyroscope measurements and send stimulation parameters to a hybrid vestibular-cochlear implant in real-time. To match natural vestibular latencies, the time from sensor input to stimulation output should not exceed 6.5 ms. We describe a system based on National Instrument's CompactRIO platform that can meet this requirement and also offers floating point precision for advanced transfer functions. It is designed for acute clinical interventions, and is sufficiently powerful and flexible to serve as a development platform for evaluating prosthetic control strategies. Amplitude and pulse frequency modulation to predetermined functions or sensor inputs have been validated. The system has been connected to human patients, who each have received a modified MED-EL cochlear implant for vestibular stimulation, and patient tests are ongoing.
This study introduces a novel algorithm to detect unexpected slipping-like perturbations based on the comparison between actual leg joint angles and those predicted by a pool of adaptive oscillators. The approach grounds on the hypothesis that during postural transitions, the difference between these datasets diverges and can early signal that the dynamic balance is challenged. To test this hypothesis, leg joint angles of twelve healthy young participants were recorded while undergoing four different perturbations delivered during steady locomotion. Joint angles were estimated after spanning the whole domain of the adaptive oscillator dynamics. Results confirmed that the implemented strategy allows to early detect a postural transition induced by a slipping-like perturbation: the best performance is represented by a mean detection time ranging between 150 and 250 ms and a low rate (lower than 10%) of false alarms. On the whole, the proposed approach is efficient even if it is based on a quite simple threshold-based algorithm. Moreover, it does not need any falling-based training before being implemented, is not computationally heavy, and is not subject dependent. Finally, since it is based on leg joint angles, it appears well suited to be implemented in lower-limb orthoses/prostheses already equipped with joint position sensors.
This paper discusses the reasons why evidence of clinical effectiveness is not enough to facilitate adequate adoption of robotic technologies for upper-limb neurorehabilitation. The paper also provides a short review of the state of the art technologies. In particular, the paper highlights the barriers to the adoption of these technologies by the markets in which they are, or should be, deployed. On the other hand, the paper explores how low rates of adoption may depend on communication biases between the producers of the technologies and potential adopters. Finally, it is shown that, although technology-efficacy issues are usually well-documented, barriers to adoption also originate from the lack of solid evidence of the economic implications of the new technologies.
Compensating for the effect of gravity by providing arm-weight support (WS) is a technique often utilized in the rehabilitation of patients with neurological conditions such as stroke to facilitate the performance of arm movements during therapy. Although it has been shown that, in healthy subjects as well as in stroke survivors, the use of arm WS during the performance of reaching movements leads to a general reduction, as expected, in the level of activation of upper limb muscles, the effects of different levels of WS on the characteristics of the kinematics of motion and of the activity of upper limb muscles have not been thoroughly investigated before.
Hand loss is a highly disabling event that markedly affects the quality of life. To achieve a close to natural replacement for the lost hand, the user should be provided with the rich sensations that we naturally perceive when grasping or manipulating an object. Ideal bidirectional hand prostheses should involve both a reliable decoding of the user's intentions and the delivery of nearly "natural" sensory feedback through remnant afferent pathways, simultaneously and in real time. However, current hand prostheses fail to achieve these requirements, particularly because they lack any sensory feedback. We show that by stimulating the median and ulnar nerve fascicles using transversal multichannel intrafascicular electrodes, according to the information provided by the artificial sensors from a hand prosthesis, physiologically appropriate (near-natural) sensory information can be provided to an amputee during the real-time decoding of different grasping tasks to control a dexterous hand prosthesis. This feedback enabled the participant to effectively modulate the grasping force of the prosthesis with no visual or auditory feedback. Three different force levels were distinguished and consistently used by the subject. The results also demonstrate that a high complexity of perception can be obtained, allowing the subject to identify the stiffness and shape of three different objects by exploiting different characteristics of the elicited sensations. This approach could improve the efficacy and "life-like" quality of hand prostheses, resulting in a keystone strategy for the near-natural replacement of missing hands.
Independent Component Analysis (ICA) is a widely applied data-driven method for parsing brain and non-brain EEG source signals, mixed by volume conduction to the scalp electrodes, into a set of maximally temporally and often functionally independent components (ICs). Many ICs may be identified with a precise physiological or non-physiological origin. However, this process is hindered by partial instability in ICA results that can arise from noise in the data. Here we propose RELICA (RELiable ICA), a novel method to characterize IC reliability within subjects. RELICA first computes IC "dipolarity" a measure of physiological plausibility, plus a measure of IC consistency across multiple decompositions of bootstrap versions of the input data. RELICA then uses these two measures to visualize and cluster the separated ICs, providing a within-subject measure of IC reliability that does not involve checking for its occurrence across subjects. We demonstrate the use of RELICA on EEG data recorded from 14 subjects performing a working memory experiment and show that many brain and ocular artifact ICs are correctly classified as "stable" (highly repeatable across decompositions of bootstrapped versions of the input data). Many stable ICs appear to originate in the brain, while other stable ICs account for identifiable non-brain processes such as line noise. RELICA might be used with any linear blind source separation algorithm to reduce the risk of basing conclusions on unstable or physiologically un-interpretable component processes.
The vestibular system plays a crucial role in the multisensory control of balance. When vestibular function is lost, essential tasks such as postural control, gaze stabilization, and spatial orientation are limited and the quality of life of patients is significantly impaired. Currently, there is no effective treatment for bilateral vestibular deficits. Research efforts both in animals and humans during the last decade set a solid background to the concept of using electrical stimulation to restore vestibular function. Still, the potential clinical benefit of a vestibular neuroprosthesis has to be demonstrated to pave the way for a translation into clinical trials. An important parameter for the assessment of vestibular function is the vestibulo-ocular reflex (VOR), the primary mechanism responsible for maintaining the perception of a stable visual environment while moving. Here we show that the VOR can be artificially restored in humans using motion-controlled, amplitude modulated electrical stimulation of the ampullary branches of the vestibular nerve. Three patients received a vestibular neuroprosthesis prototype, consisting of a modified cochlear implant providing vestibular electrodes. Significantly higher VOR responses were observed when the prototype was turned ON. Furthermore, VOR responses increased significantly as the intensity of the stimulation increased, reaching on average 79% of those measured in healthy volunteers in the same experimental conditions. These results constitute a fundamental milestone and allow us to envision for the first time clinically useful rehabilitation of patients with bilateral vestibular loss.
The aim of this study was to identify the best subset of body segments that provides for a rapid and reliable detection of the transition from steady walking to a slipping event. Fifteen healthy young subjects managed unexpected perturbations during walking. Whole-body 3D kinematics was recorded and a machine learning algorithm was developed to detect perturbation events. In particular, the linear acceleration of all the body segments was parsed by Independent Component Analysis and a Neural Network was used to classify walking from unexpected perturbations. The Mean Detection Time (MDT) was 351±123 ms with an Accuracy of 95.4%. The procedure was repeated with data related to different subsets of all body segments whose variability appeared strongly influenced by the perturbation-induced dynamic modifications. Accordingly, feet and hands accounted for most data information and the performance of the algorithm were slightly reduced using their combination. Results support the hypothesis that, in the framework of the proposed approach, the information conveyed by all the body segments is redundant to achieve effective fall detection, and suitable performance can be obtained by simply observing the kinematics of upper and lower distal extremities. Future studies are required to assess the extent to which such results can be reproduced in older adults and in different experimental conditions.
Epidural electrical stimulation (EES) of lumbosacral segments can restore a range of movements after spinal cord injury. However, the mechanisms and neural structures through which EES facilitates movement execution remain unclear. Here, we designed a computational model and performed in vivo experiments to investigate the type of fibers, neurons, and circuits recruited in response to EES. We first developed a realistic finite element computer model of rat lumbosacral segments to identify the currents generated by EES. To evaluate the impact of these currents on sensorimotor circuits, we coupled this model with an anatomically realistic axon-cable model of motoneurons, interneurons, and myelinated afferent fibers for antagonistic ankle muscles. Comparisons between computer simulations and experiments revealed the ability of the model to predict EES-evoked motor responses over multiple intensities and locations. Analysis of the recruited neural structures revealed the lack of direct influence of EES on motoneurons and interneurons. Simulations and pharmacological experiments demonstrated that EES engages spinal circuits trans-synaptically through the recruitment of myelinated afferent fibers. The model also predicted the capacity of spatially distinct EES to modulate side-specific limb movements and, to a lesser extent, extension versus flexion. These predictions were confirmed during standing and walking enabled by EES in spinal rats. These combined results provide a mechanistic framework for the design of spinal neuroprosthetic systems to improve standing and walking after neurological disorders.
. Neurorehabilitation protocols based on the use of robotic devices have recently shown to provide promising clinical results. However, their efficacy is still limited because of the poor comprehension of the mechanisms at the basis of functional enhancements.
Decades of technological developments have populated the field of neuroprosthetics with myriad replacement strategies, neuromodulation therapies, and rehabilitation procedures to improve the quality of life for individuals with neuromotor disorders. Despite the few but impressive clinical successes, and multiple breakthroughs in animal models, neuroprosthetic technologies remain mainly confined to sophisticated laboratory environments. We summarize the core principles and latest achievements in neuroprosthetics, but also address the challenges that lie along the path toward clinical fruition. We propose a pragmatic framework to personalize neurotechnologies and rehabilitation for patient-specific impairments to achieve the timely dissemination of neuroprosthetic medicine.
Matrix factorization algorithms are increasingly used to extract meaningful information from multivariate EMG datasets. However a key issue is the selection of the number of synergies (i.e., model order) to retain. In this preliminary work a set of criteria, based on Independent Component Analysis, was developed to determine the number of synergies to extract from a multivariate EMG dataset, and applied on EMG signals acquired from 12 leg muscles during walking at different cadences (40, 60, …, 140 strides per minute) in young and elderly subjects. The method was tested on ad-hoc created datasets with a predetermined number of embedded sources and amplitude of added noise. Young subjects walking patterns are explained by a number of synergies not significantly different with respect to elderly subjects. The inter-subject variability is greater at high (elderly) and low (young and elderly) cadences suggesting that the walking pattern is more stable at central frequencies. The type of preprocessing influences the number of underlying synergies: an increased number of independent components is needed to explain the variability of unfiltered data. The proposed method could serve as a guideline to scientists in the evaluation of walking performance. Further developments will include a validation of the method and its extension to other factorization algorithms.
After a stroke, patients show significant modifications of neural control of movement, such as abnormal muscle co-activation, and reduced selectivity and modulation of muscle activity. Nonetheless, results reported in literature do not allow to unequivocally explain whether and, in case, how a cerebrovascular accident affects muscle synergies underlying the control of the upper limb. These discrepancies suggest that a complete understanding of the modular re-organization of muscle activity due to a stroke is still lacking. This pilot study aimed at investigating the effects of the conjunction between the natural ongoing of the pathology and the intense robot-mediated treatment on muscle synergies of the paretic upper limb of subacute post-stroke patients.
In this conceptual review, we highlight our strategy for, and progress in the development of corticospinal neuroprostheses for restoring locomotor functions and promoting neural repair after thoracic spinal cord injury in experimental animal models. We specifically focus on recent developments in recording and stimulating neural interfaces, decoding algorithms, extraction of real-time feedback information, and closed-loop control systems. Each of these complex neurotechnologies plays a significant role for the design of corticospinal neuroprostheses. Even more challenging is the coordinated integration of such multifaceted technologies into effective and practical neuroprosthetic systems to improve movement execution, and augment neural plasticity after injury. In this review we address our progress in rodent animal models to explore the viability of a technology-intensive strategy for recovery and repair of the damaged nervous system. The technical, practical, and regulatory hurdles that lie ahead along the path toward clinical applications are enormous - and their resolution is uncertain at this stage. However, it is imperative that the discoveries and technological developments being made across the field of neuroprosthetics do not stay in the lab, but instead reach clinical fruition at the fastest pace possible.
Several studies investigating the use of electromyographic (EMG) signals in robot-based stroke neuro-rehabilitation to enhance functional recovery. Here we explored whether a classical EMG-based patterns recognition approach could be employed to predict patients intentions while attempting to generate goal-directed movements in the horizontal plane.
MUNDUS is an assistive framework for recovering direct interaction capability of severely motor impaired people based on arm reaching and hand functions. It aims at achieving personalization, modularity and maximization of the users direct involvement in assistive systems. To this, MUNDUS exploits any residual control of the end-user and can be adapted to the level of severity or to the progression of the disease allowing the user to voluntarily interact with the environment. MUNDUS target pathologies are high-level spinal cord injury (SCI) and neurodegenerative and genetic neuromuscular diseases, such as amyotrophic lateral sclerosis, Friedreich ataxia, and multiple sclerosis (MS). The system can be alternatively driven by residual voluntary muscular activation, head/eye motion, and brain signals. MUNDUS modularly combines an antigravity lightweight and non-cumbersome exoskeleton, closed-loop controlled Neuromuscular Electrical Stimulation for arm and hand motion, and potentially a motorized hand orthosis, for grasping interactive objects.
This study investigated the hypothesis that the coupled contribution of all body segments to the whole-body response during both walking and managing unexpected perturbations is characterized by similar features which do not depend on the laterality (i.e., right versus left sides), but can be influenced by the direction (e.g., north, east, south, etc.) of the perturbation. The whole-body angular momentum was estimated as summation of segmental angular momenta, while 15 young adults managed ten unexpected unilateral perturbations during walking. Then, the Principal component analysis was used to extract primitive features describing intersegment coordination. Results showed that intersegment coupling was similar even though the reactive response to the perturbations elicited more consistent motor schemes across body segments than during walking, especially in the frontal plane. The direction of the perturbation significantly affected angular momentum regulation documenting the attitude of the central nervous system to interpret multiple sensory inputs in order to produce context-dependent reactive responses. With respect to the side, results highlighted anisotropic features of the elicited motor schemes that seemed to depend on subjects dominance. Finally, results confirm that the coordination of upper and lower body segments is synergistically achieved strengthening the hypothesis that it may result from common neural pathways.
Spinal circuits play an important role in the generation of rhythmic motor activity, intermediating between descending signals and peripheral sensory information. The study of these circuits can provide a better understanding of the control mechanisms during the execution of cyclic motor tasks in healthy subjects or in patients with motor deficits due to a neurological disease. This work shows preliminary results regarding the estimation of spinal cord activity of post-stroke subjects obtained from the EMG signals by improving the computational model. This new model allows a better quantitative evaluation of motor performance in clinical contexts.
The aim of the present pilot study is to investigate the hypothesis that fall detection systems based on sensors placed on the distal segments of the body are more effective than solution based on placing sensors on the trunk. To test this hypothesis, we observed the contribution of all body segments to the 3D angular momentum. Five healthy adults were enrolled for the experimental sessions. A set of 39 spherical markers was located on body landmarks and subjects underwent perturbed walking while a Motion Analysis System recorded 3D kinematics. From a biomechanical model, the angular momentum pattern related to each body segment was estimated. Data were post-processed with a threshold-based algorithm used to detect which among body segments allows detect as soon as possible and with limited false alarms the perturbation. Results showed that hands-forearms and chest-head are the most sensitive to external moments orientated along respectively the anterior-posterior and medio-lateral directions.
During the development of a neural prosthesis, various ethical aspects have to be considered. These range from the basic design of the prosthesis and manufacturing of the various components and the system using biocompatible materials to extensive in vitro and in vivo testing and investigations in the animal model, before taking the final step and going to human trials. As medical systems, neural prostheses have to be proven absolutely safe before considering any clinical study. In this work, the various steps accompanying the development are described taking the example of a vestibular prosthesis currently developed within the European project CLONS.
Implantable interfaces are essential components of vestibular neural prostheses. They interface the biological system with electrical stimulation that is used to restore transfer of vestibular information. Regarding the anatomical situation special 3D structures are required. In this paper, the design and the manufacturing process of a novel 3D hybrid microelectrode structure as interface to the human vestibular system are described. Photolithography techniques, assembling technology and rapid prototyping are used for manufacturing.
Tungsten microneedles are currently used to insert neural electrodes into living peripheral nerves. However, the biomechanics underlying these procedures is not yet well characterized. For this reason, the aim of this work was to model the interactions between these microneedles and living peripheral nerves. A simple mathematical framework was especially provided to model both compression of the external layer of the nerve (epineurium) and the interactions resulting from penetration of the main shaft of the microneedle inside the living nerves. The instantaneous Youngs modulus, compression force, the work needed to pierce the tissue, puncturing pressure, and the dynamic friction coefficient between the tungsten microneedles and living nerves were quantified starting from acute experiments, aiming to reproduce the physical environment of real implantations. Indeed, a better knowledge of the interactions between microneedles and peripheral nerves may be useful to improve the effectiveness of these insertion techniques, and could represent a key factor for designing robot-assisted procedures tailored for peripheral nerve insertion.
Neuroprostheses based on electrical stimulation could potentially help disabled persons. They are based on neural interface that aim at creating an intimate contact with neural cells. The efficacy of neuroprostheses can be improved by increasing the selectivity of the neural interfaces used to stimulate specific subsets of cells. Selectivity is strongly influenced by interface design. Computer models can be useful for exploring the high dimensional space of design parameters with the aim to provide guidelines for the development of more efficient electrodes, with minimal animal use and optimization of manufacturing processes. The purpose of this study was to implement a realistic model of the performance of a transverse intrafascicular multichannel electrode (TIME) implanted into the rat sciatic nerve. A realistic finite element method (FEM) model was developed taking into account the anatomical and physiological features of the rat sciatic nerve. Electric potentials were calculated and interpolated voltages were applied to the model of a rat sciatic nerve axon, based on experimental biophysical data. Results indicate that high intra-fascicular and inter-fascicular selectivity values with low current levels can be achieved with TIMEs. The selectivity of TIMEs was also compared to an extraneural electrode, showing that higher selectivity with less current can be obtained. Using this model, the robustness of electrode performances for translational and rotational displacements were evaluated.
In this work we address the use of realtime cortical recordings for the generation of coherent, reliable and robust motor activity in spinal-lesioned animals through selective intraspinal microstimulation (ISMS). The spinal cord of adult rats was hemisectioned and groups of multielectrodes were implanted in both the central nervous system (CNS) and the spinal cord below the lesion level to establish a neural system interface (NSI). To test the reliability of this new NSI connection, highly repeatable neural responses recorded from the CNS were used as a pattern generator of an open-loop control strategy for selective ISMS of the spinal motoneurons. Our experimental procedure avoided the spontaneous non-controlled and non-repeatable neural activity that could have generated spurious ISMS and the consequent undesired muscle contractions. Combinations of complex CNS patterns generated precisely coordinated, reliable and robust motor actions.
This work defines an incompressible, hyperelastic theory of anisotropic soft materials at finite strains, which is tested by application to the experimental response of fiber-reinforced rubber materials. The experimental characterization is performed using a uniaxial testing device with optical measures of the deformation, using two different reinforcing materials on a ground rubber matrix. In order to avoid non-physical responses of the underlying structural components of the material, the kinematics of the deformation are described using a novel deformation tensor, which ensures physical consistency at large strains. A constitutive relation for incompressible fiber-reinforced materials is presented, while issues of stability and ellipticity for the hyperelastic solution are considered to impose necessary restrictions on the constitutive parameters. The theoretical predictions of the proposed model are compared with the anisotropic experimental responses, showing high fitting accuracy in determining the mechanical parameters of the model. The constitutive theory is suitable to account for the anisotropic response at large compressive strains, opening perspectives for many applications in tissue engineering and biomechanics.
Functional electrical stimulation (FES) is limited by the rapid onset of muscle fatigue caused by localized nerve excitation repeatedly activating only a subset of motor units. The purpose of this study was to investigate reducing fatigue by sequentially changing, pulse by pulse, the area of stimulation using multiple surface electrodes that cover the same area as one electrode during conventional stimulation. Paralyzed triceps surae muscles of an individual with complete spinal cord injury were stimulated, via the tibial nerve, through four active electrodes using spatially distributed sequential stimulation (SDSS) that was delivered by sending a stimulation pulse to each electrode one after another with 90° phase shift between successive electrodes. For comparison, single electrode stimulation was delivered through one active electrode. For both modes of stimulation, the resultant frequency to the muscle as a whole was 40 Hz. Isometric ankle torque was measured during fatiguing stimulations lasting 2 min. Each mode of stimulation was delivered a total of six times over 12 separate days. Three fatigue measures were used for comparison: fatigue index (final torque normalized to maximum torque), fatigue time (time for torque to drop by 3 dB), and torque-time integral (over the entire trial). The measures were all higher during SDSS (P < 0.001), by 234, 280, and 171%, respectively. The results are an encouraging first step toward addressing muscle fatigue, which is one of the greatest problems for FES.
In this paper a self-opening intrafascicular neural interface (SELINE) has been modeled using both a theoretical approach and a Finite Element (FE) analysis. This innovative self opening interface has several potential advantages such as: higher selectivity due to its three-dimensional structure and efficient anchorage system. Mechanical, structural and micro-technological issues have been considered to obtain an effective design of the electrode, as a feasibility study of the self-opening approach. A simple framework has been provided to model the insertion and partial retraction into peripheral nerves, resulting in the opening of wings. This integrated approach results in a rational procedure to optimize kinematics, geometry, and structural properties of peripheral interfaces. The design and feasibility study carried out in this work can potentially assure a correct behavior and dimensioning of the neural interface: in this way anomalous breakage should be avoided while mechanical and geometrical biocompatibility should increase.
Do central and peripheral motor pathways associated with an amputated limb retain at least some functions over periods of years? This problem could be addressed by evaluating the response patterns of nerve signals from peripheral motor fibers during transcranial magnetic stimulation (TMS) of corticospinal tracts. The aim of this study was to record for the first time TMS-related responses from the nerves of a left arm stump of an amputee via intrafascicular longitudinal flexible multi-electrodes (tfLIFE4) implanted for a prosthetic hand control. After tfLIFE4 implant in the stump median and ulnar nerves, TMS impulses of increasing intensity were delivered to the contralateral motor cortex while tfLIFE4 recordings were carried out. Combining TMS of increasing intensity and tfLIFE4 electrodes recordings, motor nerve activity possibly related to the missing limb motor control and selectively triggered by brain stimulation without significant electromyographic contamination was identified. These findings are entirely original and indicate that tfLIFE4 signals are clearly driven from M1 stimulation, therefore witnessing the presence in the stump nerves of viable motor signals from the CNS possibly useful for artificial prosthesis control.
We employ simple geometrical rules to design a set of nanotopographies able to interfere with focal adhesion establishment during neuronal differentiation. Exploiting nanoimprint lithography techniques on cyclic-olefin-copolymer films, we demonstrate that by varying a single topographical parameter the orientation and maturation of focal adhesions can be finely modulated yielding independent control over the final number and the outgrowth direction of neurites. Taken together, this report provides a novel and promising approach to the rational design of biocompatible textured substrates for tissue engineering applications.
The restoration of complex hand functions by creating a novel bidirectional link between the nervous system and a dexterous hand prosthesis is currently pursued by several research groups. This connection must be fast, intuitive, with a high success rate and quite natural to allow an effective bidirectional flow of information between the users nervous system and the smart artificial device. This goal can be achieved with several approaches and among them, the use of implantable interfaces connected with the peripheral nervous system, namely intrafascicular electrodes, is considered particularly interesting.
Neural interfaces are aimed at creating an intimate contact with neural cells, either to stimulate the nerves or to record neural signals. This would allow the development of neurocontrolled artificial devices. The quality of these systems can be improved by increasing the selectivity of the neural interfaces used to stimulate or to record the activity of specific subsets of cells. Hence selectivity is of major importance for successful applications. The selectivity of these devices is a key issue and could be strongly influenced by the design of the microelectrode used. In this paper, a novel integrated FEM/Biophysical model based on anatomical and immunochemistry data providing guidelines for the design of more effective intraneural electrodes is used in studying the influence of active site shapes on the quality of stimulation and some preliminary results are also shown.
The possible control of axonal outgrowth during neural regeneration could be very useful not only from a neurobiological point of view, but also in the field of neural interfaces. In this manuscript, simulations are presented which investigate the possibility of guiding axons by using a hybrid approach based on the combined used of a chemical model and of a genetic algorithm. Microspheres embedding chemical cues on the basis of information provided by a genetic algorithm are placed to impose a desired trajectory on the axons. Two kinds of simulations were carried out: (i) tracking of linear trajectories; (ii) tracking of trajectories, which were reconstructed from real axonal extension. The results achieved during the simulations seem to confirm the possible use of this approach to guide axonal outgrowth, being the obtained trajectories congruent to possible actual situations. Moreover, the model can be easily extended to a three-dimensional environment.
Recent findings have shown that neural circuits located in the spinal cord drive muscular activations during locomotion while intermediating between descending signals and peripheral sensory information. This relationship could be modified by the natural aging process. To address this issue, the activity of 12 ipsilateral leg muscles was analyzed in young and elderly people (7 subjects per group) while walking at six different cadences (40-140 steps/min). These signals were used to extract synergies underlying muscle activation and to map the motoneuronal activity of the pools belonging to the lumbosacral enlargement (L(2)-S(2)). The comparison between the two groups showed that neither temporal patterning of motor primitives nor muscles loading synergies seemed to be significantly affected by aging. Conversely, as the cadence increased, spinal maps differ significantly between the groups, showing higher and scattered activity during the whole gait cycle in elders and well-defined bursts in young subjects. The results suggested that motor primitives lead the synchronization of muscle activation mainly depending on the biomechanical demand of the locomotion; hence they are not significantly affected by aging. Nevertheless, at the spinal cord level, biomechanical requirements, peripheral afference, and descending inputs are differently integrated between the two groups, probably reflecting age-related changes of both nervous system and motor control strategies during locomotion.
In this article, we focus on the least invasive interface: transcutaneous ES (TES), i.e., the use of surface electrodes as an interface between the stimulator and sensory-motor systems. TES is delivered by a burst of short electrical charge pulses applied between pairs of electrodes positioned on the skin. Monophasic or charge-balanced biphasic (symmetric or asymmetric) stimulation pulses can be delivered. The latter ones have the advantage to provide contraction force while minimizing tissue damage.
Several groups have shown that the performance of motor neuroprostheses can be significantly improved by detecting specific sensory events related to the ongoing motor task (e.g., the slippage of an object during grasping). Algorithms have been developed to achieve this goal by processing electroneurographic (ENG) afferent signals recorded by using single-channel cuff electrodes. However, no efforts have been made so far to understand the number and type of detectable sensory events that can be differentiated from whole nerve recordings using this approach.
The humanoid robot WE4-RII was designed to express human emotions in order to improve human-robot interaction. We can read the emotions depicted in its gestures, yet might utilize different neural processes than those used for reading the emotions in human agents.
The principle underlying this project is that, despite nervous reorganization following upper limb amputation, original pathways and CNS relays partially maintain their function and can be exploited for interfacing prostheses. Aim of this study is to evaluate a novel peripheral intraneural multielectrode for multi-movement prosthesis control and for sensory feed-back, while assessing cortical reorganization following the re-acquired stream of data.
One of the main scientific and technological challenges of rehabilitation bioengineering is the development of innovative methodologies, based on the use of appropriate technological devices, for an objective assessment of patients undergoing a rehabilitation treatment. Such tools should be as fast and cheap to use as clinical scales, which are currently the daily instruments most widely used in the routine clinical practice.
Important advancements have been recently achieved in the field of neural interfaces to restore lost sensory and motor functions. The aim of this letter was to develop an innovative approach to increase the selectivity and the lifetime of polyimide-based intrafascicular electrodes. The main idea was to obtain a neural interface that is able to restore a good signal quality by improving the electrical connection between the active sites and the surrounding axons. The high flexibility of polyimide-based neural interfaces allows to embed microactuators in the interface core and achieve desired microdisplacements of the active sites. Nearly equiatomic nickel-titanium alloy was selected as a microactuator because of its shape memory effect. A single TiNi thin film was obtained by dc magnetron sputtering, and was segmented into four distinct sectors. This solution allowed the independent actuation of the different active sites (multiactuation). A corrugated profile was impressed to the new actuated intraneural (ACTIN) interface. The active sites were positioned in correspondence to the peaks of the corrugation, thus maximizing the effects of the single actuations. The technological results, the electrical properties, the thermal behavior, and eventually, the actuation performances of the current ACTIN prototype are shown and discussed. The actuation cycle was thermally compatible for biomedical applications. Promising results were obtained from the current ACTIN prototype with an average controlled movement of 7 microm of the peaks.
Considerable scientific and technological efforts have been devoted to develop neuroprostheses and hybrid bionic systems that link the human nervous system with electronic or robotic prostheses, with the main aim of restoring motor and sensory functions in disabled patients. Such developments have also the potential to be applied to normal human beings to improve their physical capabilities for bidirectional control and feedback of machines. A number of neuroprostheses use interfaces with peripheral nerves or muscles for neuromuscular stimulation and signal recording. This chapter provides a general overview of the peripheral neural interfaces available and their use from research to clinical application in controlling artificial and robotic prostheses and in developing neuroprostheses. Extraneural electrodes, such as cuff and epineurial electrodes, provide simultaneous interface with many axons in the nerve, whereas intrafascicular, penetrating, and regenerative electrodes may selectively contact small groups of axons within a nerve fascicle. Biological and technical issues are reviewed relative to the problems of electrode design and tissue injury. The last sections review different strategies for the use of peripheral neural interfaces in biomedical applications.
Reach-to-grasp tasks are composed of several actions that are more and more considered as simultaneously controlled by the central nervous system in a feedforward manner (at least for well-known activities). If this hypothesis is correct, during prehension tasks, the activity of proximal muscles (and not only of the distal ones used to control finger movements) is modulated according to the kind of object to be grasped and its position. This means that different objects could be identified by processing the electromyographic (EMG) signals recorded from proximal muscles. In this paper, specific experiments have been carried out to support this hypothesis in able-bodied subjects. The results achieved seem to confirm this possibility by showing that the activation of proximal muscles can be statistically different for different grip types. This finding supports the hypothesis that proximal and distal muscles are simultaneously controlled during reaching and grasping. Moreover, this kind of information could allow the development of an EMG-based control strategy based on the natural muscular activities selected by the central nervous system.
The use of polymeric carriers containing dispersed magnetic nanocrystalline particles for targeted delivery of drugs in clinical practice has attracted the interest of the scientific community. In this paper a system comprised of alginate microparticles with a core of magnetite and carrying nerve growth factor (NGF) is described. The magnetic properties of these microspheres, typical of superparamagnetic materials, allow precise and controlled delivery to the intended tissue environment. Experiments carried out on PC12 cells with magnetic alginate microspheres loaded with NGF have confirmed the induction of cell differentiation which is strongly dependent on the distance from the microsphere cluster. In addition, finite element modelling (FEM) of the release profile from the microspheres in culture, indicated the possibility of creating defined and predictable NGF gradients from the loaded microspheres. These observations on the carriage and release of growth factors by the proposed microparticles open new therapeutic options for both neuronal regeneration and of the development of effective neuronal interfaces.
Array electrodes are a promising technology that is likely to bring transcutaneous electrical stimulation (TES) a step forward. The dynamic adaptation of electrode size and position helps to simplify the use of electrical stimulation systems and to increase their clinical efficacy. However, up to now array electrodes were built by trial and error and it is unclear how, for example, the gaps between the array elements or the resistivity of the electrode-skin interface material influence the current distribution. A TES model that comprises a finite element model and a nerve model has been used to analyze the influence of array electrode gaps and gel resistivities on nerve activation. Simulation results indicate that the resistivity of the electrode-skin interface layer should be adapted depending on the size of the gaps between the array elements. Furthermore, the gap sizes should be smaller than 3mm in order to keep losses small.
Both ageing and speed definitely affect gait patterns. Since most of the comparisons between young and elderly people while walking have been carried out at different "self-selected" speeds, results might be biased by a lack of control of the effects of both the concomitant issues. Therefore, further investigations aimed at separating the influence of both the sources of variability are required.
This paper describes a noninvasive electromyography (EMG) signal-based computer interface and a performance evaluation method based on Fitts law. The EMG signals induced by volitional wrist movements were acquired from four sites in the lower arm to extract users intentions, and six classes of wrist movements were distinguished using an artificial neural network. Using the developed interface, a user can move the cursor, click buttons, and type text on a computer. The test setup was built to evaluate the developed interface, and the mouse was tested by five volunteers with intact limbs. The performance of the developed computer interface and the mouse was tested at 1.299 and 7.733 b/s, respectively, and these results were compared with the performance of a commercial noninvasive brain signal interface (0.386 b/s). The results show that the developed interface performed better than the commercial interface, but less satisfactorily than a computer mouse. Although some issues remain to be resolved, the developed EMG interface has the potential to help people with motor disabilities to access computers and Internet environments in a natural and intuitive manner.
In this article, a carbon nanotube (CNT) array-based system combined with a polymer thin film is proposed as an effective drug release device directly at cellular level. The polymeric film embedded in the CNT array is described and characterized in terms of release kinetics, while in vitro assays on PC12 cell line have been performed in order to assess the efficiency and functionality of the entrapped agent (neural growth factor, NGF). PC12 cell differentiation, following incubation on the CNT array embedding the alginate delivery film, demonstrated the effectiveness of the proposed solution. The achieved results indicate that polymeric technology could be efficiently embedded in CNT array acting as drug delivery system at cellular level. The implication of this study opens several perspectives in particular in the field of neurointerfaces, combining several functions into a single platform.
Muscle synergies are considered as a potential strategy to reduce the computational workload undergoing the estimation of muscle activity during different motor tasks. They are usually extracted by means of algebraic factorization algorithms able to capture the greatest communality of a set of electromyographic (EMG) signals. Usually EMG signals are pooled across different sub-movements (e.g., going forward and backward during reaching) in order to increase the complexity of the data set and, consequently, capture the maximum communality. Despite of these, this preliminary study was designed to investigate how the communality of EMG signals can be explained looking at narrow subset of recorded signals. Results corroborate the hypothesis that using a suitable subset of the whole dataset can significantly modify the values of weight coefficients. In this regard, further methodological investigations of algorithms adopted for synergy extraction are still required.
Rotational cues in patients that suffer from bilateral vestibular loss can be delivered by vestibular prosthesis. Even though great efforts towards the development of a vestibular implant have been made, many parameters have still to be optimized. Numerical simulations of the neural activation during electrical stimulation can give important indications about the optimal electrode insertion site, stimulation waveform and electrode configuration, in terms of the highest selectivity. The first step of this type of numerical simulation requires the digital reconstruction of the human inner ear and the calculation of the spatial electrical potential distribution by means of finite-element methods.
In the recent past several invasive cortical neuroprostheses have been developed. Signals recorded from the motor cortex (area MI) have been decoded and used to control computer cursors and robotic devices. Nevertheless, few attempts have been carried out to predict different grips.A Support Vector Machines (SVMs) classifier has been trained for a continuous decoding of four/six grip types using signals recorded in two monkeys from motor neurons of the ventral premotor cortex (area F5) during a reach-to-grasp task.
Phantom limb pain (PLP) is a chronic condition that develops in the majority of amputees. The underlying mechanisms are not completely understood, and thus, no treatment is fully effective. Based on recent studies, we hypothesize that electrical stimulation of afferent nerves might alleviate PLP by giving sensory input to the patient if nerve fibers can be activated selectively. The critical component in this scheme is the implantable electrode structure. We present a review of a novel electrode concept to distribute highly selective electrode contacts over the complete cross section of a peripheral nerve to create a distributed activation of small nerve fiber ensembles at the fascicular level, the transverse intrafascicular multichannel nerve electrode (TIME). The acute and chronic implantations in a small animal model exhibited a good surface and structural biocompatibility as well as excellent selectivity. Implantation studies on large animal models that are closer to human nerve size and anatomical complexity have also been conducted. They proved implant stability and the ability to selectively activate nerve fascicles in a limited proximity to the implant. These encouraging results have opened the way forward for human clinical trials in amputees to investigate the effect of selective electrical stimulation on PLP.
Over the past decades, a large number of robotic platforms have been developed which provide rehabilitative treatments aimed at recovering walking abilities in post-stroke patients. Unfortunately, they do not significantly influence patients performance after three months from the accident. One of the main reasons underlying this result seems to be related to the time of intervention. Specifically, although experimental evidences suggest that early (i.e., first days after the injury) and intense neuro-rehabilitative treatments can significantly favor the functional recovery of post-stroke patients, robots require patients to be verticalized. Consequently, this does not allow them to be treated immediately after the trauma. This paper introduces a new robotic platform, named NEUROBike, designed to provide neuro-rehabilitative treatments to bedridden patients. It was designed to provide an early and well-addressed rehabilitation therapy, in terms of kinesiology, efforts, and fatigue, accounting for exercises functionally related to daily motor tasks. For this purpose, kinematic models of leg-joint angular excursions during both walking and sit-to-stand were developed and implemented in control algorithms leading both passive and active exercises. Finally, a set of pilot tests was carried out to evaluate the performance of the robotic platform on healthy subjects.
Studying the responses in human behaviour to external perturbations during daily motor tasks is of key importance for understanding mechanisms of balance control and for investigating the functional response of targeted subjects. Experimental platforms as far developed entail a low number of perturbations and, only in few cases, have been designed to measure variables used at run time to trigger events during a certain motor task.
The F11 hybridoma, a dorsal root ganglion-derived cell line, was used to investigate the response of nociceptive sensory neurons to nanotopographical guidance cues. This established this cell line as a model of peripheral sensory neuron growth for tissue scaffold design. Cells were seeded on substrates of cyclic olefin copolymer (COC) films imprinted via nanoimprint lithography (NIL) with a grating pattern of nano-scale grooves and ridges. Different ridge widths were employed to alter the focal adhesion formation, thereby changing the cell/substrate interaction. Differentiation was stimulated with forskolin in culture medium consisting of either 1 or 10% fetal bovine serum (FBS). Per medium condition, similar neurite alignment was achieved over the four day period, with the 1% serum condition exhibiting longer, more aligned neurites. Immunostaining for focal adhesions found the 1% FBS condition to also have fewer, less developed focal adhesions. The robust response of the F11 to guidance cues further builds on the utility of this cell line as a sensory neuron model, representing a useful tool to explore the design of regenerative guidance tissue scaffolds.
Half of human spinal cord injuries lead to chronic paralysis. Here, we introduce an electrochemical neuroprosthesis and a robotic postural interface designed to encourage supraspinally mediated movements in rats with paralyzing lesions. Despite the interruption of direct supraspinal pathways, the cortex regained the capacity to transform contextual information into task-specific commands to execute refined locomotion. This recovery relied on the extensive remodeling of cortical projections, including the formation of brainstem and intraspinal relays that restored qualitative control over electrochemically enabled lumbosacral circuitries. Automated treadmill-restricted training, which did not engage cortical neurons, failed to promote translesional plasticity and recovery. By encouraging active participation under functional states, our training paradigm triggered a cortex-dependent recovery that may improve function after similar injuries in humans.
In the fall of 2010, the National Science Foundation, the National Institutes of Health and the U.S. Veterans Administration jointly supported a review of mobility technology in Europe. A delegation of American Scientists traveled to Europe to visit a number of research centers and engaged in a demonstration and dialogue related to the global state-of-the-art for mobility impairment rectification and augmentation. From the observations and exchanges between the U.S. delegation and host institutions, the researchers were able to derive a series of papers which are now published in this thematic series of Journal of NeuroEngineering and Rehabilitation. The papers describe the main themes of the European mobility technology research activities showing a healthy picture of research and innovation in the field.
Recently a hybrid model based on the finite element method and on a compartmental biophysical representation of peripheral nerve fibers and intraneural electrodes was developed founded on experimental physiological and histological data. The model appeared to be robust when dealing with uncertainties in parameter selection. However, an experimental validation of the findings provided by the model is required to fully characterize the potential of this approach. The recruitment properties of selective nerve stimulation using transverse intrafascicular multichannel electrodes (TIME) were investigated in this work in experiments with rats and were compared to model predictions. Animal experiments were performed using the same stimulation protocol as in the computer simulations in order to rigorously validate the model predictions and understand its limitations. Two different selectivity indexes were used, and new indexes for measuring electrode performance are proposed. The model predictions are in decent agreement with experimental results both in terms of recruitment curves and selectivity values. Results show that these models can be used for extensive studies targeting electrode shape design, active sites shape, and multipolar stimulation paradigms. From a neurophysiological point of view, the topographic organization of the rat sciatic nerve, on which the model was based, has been confirmed.
Robot-aided neurorehabilitation can provide intensive, repetitious training to improve upper-limb function after stroke. To be more effective, motor therapy ought to be progressive and continuously challenge the patients ability. Current robotic systems have limited customization capability and require a physiotherapist to assess progress and adapt therapy accordingly.
Vestibular prosthetics transmit angular velocities to the nervous system via electrical stimulation. Head-fixed gyroscopes measure angular motion, but the gyroscope coordinate system will not be coincident with the sensory organs the prosthetic replaces. Here we show a simple calibration method to align gyroscope measurements with the anatomical coordinate system. We benchmarked the method with simulated movements and obtain proof-of-concept with one healthy subject. The method was robust to misalignment, required little data, and minimal processing.
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