Neurorobotics for neurorehabilitation

Bionic blink improves real-time eye closure in unilateral facial paralysis

Facial paralysis is the inability to move facial muscles thereby impairing the ability to blink and make facial expressions. Depending on the localization of the nerve malfunction it is subcategorised into central or peripheral and is usually unilateral. This leads to health deficits stemming from corneal dryness and social ostracization.Objective: Electrical stimulation shows promise as a method through which to restore the blink function and as a result improve eye health. However, it is unknown whether a real-time, myoelectrically controlled, neurostimulating device can be used as assistance to this pathological condition.Approach: We developed NEURO-BLINK, a wearable robotic system, that can detect the volitional healthy contralateral blink through electromyography and electrically stimulate the impaired subcutaneous facial nerve and orbicularis oculi muscle to compensate for lost blink function. Alongside the system, we developed a method to evaluate optimal electrode placement through the relationship between blink amplitude and injected charge.Main results: Ten patients with unilateral facial palsy were enrolled in the NEURO-BLINK study, with eight completing testing under two conditions. (1) where the stimulation was cued with an auditory signal (i.e. paced controlled) and (2) synchronized with the natural blink (i.e. myoelectrically controlled). In both scenarios, overall eye closure (distance between eyelids) and cornea coverage measured with high FPS video were found to significantly improve when measured in real-time, while no significant clinical changes were found immediately after use.Significance: This work takes steps towards the development of a portable medical device for blink restoration and facial stimulation which has the potential to improve long-term ocular health.

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

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

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

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

Automated calibration of somatosensory stimulation using reinforcement learning

BACKGROUND

The identification of the electrical stimulation parameters for neuromodulation is a subject-specific and time-consuming procedure that presently mostly relies on the expertise of the user (e.g., clinician, experimenter, bioengineer). Since the parameters of stimulation change over time (due to displacement of electrodes, skin status, etc.), patients undergo recurrent, long calibration sessions, along with visits to the clinics, which are inefficient and expensive. To address this issue, we developed an automatized calibration system based on reinforcement learning (RL) allowing for accurate and efficient identification of the peripheral nerve stimulation parameters for somatosensory neuroprostheses.

METHODS

We developed an RL algorithm to automatically select neurostimulation parameters for restoring sensory feedback with transcutaneous electrical nerve stimulation (TENS). First, the algorithm was trained offline on a dataset comprising 49 subjects. Then, the neurostimulation was then integrated with a graphical user interface (GUI) to create an intuitive AI-based mapping platform enabling the user to autonomously perform the sensation characterization procedure. We assessed the algorithm against the performance of both experienced and naïve and of a brute force algorithm (BFA), on 15 nerves from five subjects. Then, we validated the AI-based platform on six neuropathic nerves affected by distal sensory loss.

RESULTS

Our automatized approach demonstrated the ability to find the optimal values of neurostimulation achieving reliable and comfortable elicited sensations. When compared to alternatives, RL outperformed the naïve and BFA, significantly decreasing the time for mapping and the number of delivered stimulation trains, while improving the overall quality. Furthermore, the RL algorithm showed performance comparable to trained experimenters. Finally, we exploited it successfully for eliciting sensory feedback in neuropathic patients.

CONCLUSIONS

Our findings demonstrated that the AI-based platform based on a RL algorithm can automatically and efficiently calibrate parameters for somatosensory nerve stimulation. This holds promise to avoid experts' employment in similar scenarios, thanks to the merging between AI and neurotech. Our RL algorithm has the potential to be used in other neuromodulation fields requiring a mapping process of the stimulation parameters.

TRIAL REGISTRATION

ClinicalTrial.gov (Identifier: NCT04217005).

Brain-Computer Interface to Deliver Individualized Multisensory Intervention for Neuropathic Pain

To unravel the complexity of the neuropathic pain experience, researchers have tried to identify reliable pain signatures (biomarkers) using electroencephalography (EEG) and skin conductance (SC). Nevertheless, their use as a clinical aid to design personalized therapies remains scarce and patients are prescribed with common and inefficient painkillers. To address this need, novel non-pharmacological interventions, such as transcutaneous electrical nerve stimulation (TENS) to activate peripheral pain relief via neuromodulation and virtual reality (VR) to modulate patients' attention, have emerged. However, all present treatments suffer from the inherent bias of the patient's self-reported pain intensity, depending on their predisposition and tolerance, together with unspecific, pre-defined scheduling of sessions which does not consider the timing of pain episodes onset. Here, we show a Brain-Computer Interface (BCI) detecting in real-time neurophysiological signatures of neuropathic pain from EEG combined with SC and accordingly triggering a multisensory intervention combining TENS and VR. After validating that the multisensory intervention effectively decreased experimentally induced pain, the BCI was tested with thirteen healthy subjects by electrically inducing pain and showed 82% recall in decoding pain in real time. Such constructed BCI was then validated with eight neuropathic patients reaching 75% online pain precision, and consequently releasing the intervention inducing a significant decrease (50% NPSI score) in neuropathic patients' pain perception. Our results demonstrate the feasibility of real-time pain detection from objective neurophysiological signals, and the effectiveness of a triggered combination of VR and TENS to decrease neuropathic pain. This paves the way towards personalized, data-driven pain therapies using fully portable technologies.

Design of an adaptable intrafascicular electrode (AIR) for selective nerve stimulation by model-based optimization

Peripheral nerve stimulation is being investigated as a therapeutic tool in several clinical scenarios. However, the adopted devices have restricted ability to obtain desired outcomes with tolerable off-target effects. Recent promising solutions are not yet employed in clinical practice due to complex required surgeries, lack of long-term stability, and implant invasiveness. Here, we aimed to design a neural interface to address these issues, specifically dimensioned for pudendal and sacral nerves to potentially target sexual, bladder, or bowel dysfunctions. We designed the adaptable intrafascicular radial electrode (AIR) through realistic computational models. They account for detailed human anatomy, inhomogeneous anisotropic conductance, following the trajectories of axons along curving and branching fascicles, and detailed biophysics of axons. The model was validated against available experimental data. Thanks to computationally efficient geometry-based selectivity estimations we informed the electrode design, optimizing its dimensions to obtain the highest selectivity while maintaining low invasiveness. We then compared the AIR with state-of-the-art electrodes, namely InterStim leads, multipolar cuffs and transversal intrafascicular multichannel electrodes (TIME). AIR, comprising a flexible substrate, surface active sites, and radially inserted intrafascicular needles, is designed to be implanted in a few standard steps, potentially enabling fast implants. It holds potential for repeatable stimulation outcomes thanks to its radial structural symmetry. When compared in-silico, AIR consistently outperformed cuff electrodes and InterStim leads in terms of recruitment threshold and stimulation selectivity. AIR performed similarly or better than a TIME, with quantified less invasiveness. Finally, we showed how AIR can adapt to different nerve sizes and varying shapes while maintaining high selectivity. The AIR electrode shows the potential to fill a clinical need for an effective peripheral nerve interface. Its high predicted performance in all the identified requirements was enabled by a model-based approach, readily applicable for the optimization of electrode parameters in any peripheral nerve stimulation scenario.

Innovative perspectives in limbic surgery using deep brain stimulation

Limbic surgery is one of the most attractive and retaken fields of functional neurosurgery in the last two decades. Psychiatric surgery emerged from the incipient work of Moniz and Lima lesioning the prefrontal cortex in agitated patients. Since the onset of stereotactic and functional neurosurgery with Spiegel and Wycis, the treatment of mental diseases gave attention to refractory illnesses mainly with the use of thalamotomies. Neurosis and some psychotic symptoms were treated by them. Several indications when lesioning the brain were included: obsessive-compulsive disorder, depression, and aggressiveness among others with a diversity of targets. The indiscriminately use of anatomical sites without enough scientific evidence, and uncertainly defined criteria for selecting patients merged with a deficiency in ethical aspects, brought a lack of procedures for a long time: only select clinics allowed this surgery around the world from 1950 to the 1990s. In 1999, Nuttin et al. began a new chapter in limbic surgery with the use of Deep Brain Stimulation, based on the experience of pain, Parkinson's disease, and epilepsy. The efforts were focused on different targets to treat depression and obsessive-compulsive disorders. Nevertheless, other diseases were added to use neuromodulation. The goal of this article is to show the new opportunities to treat neuropsychiatric diseases.

[New technologies and robotics]

The development of increasingly more complex computer and electromotor technologies enables the increasing use and expansion of robot-assisted systems in trauma surgery rehabilitation; however, the currently available devices are rarely comprehensively applied but are often used within pilot projects and studies. Different technological approaches, such as exoskeletal systems, functional electrical stimulation, soft robotics, neurorobotics and brain-machine interfaces are used and combined to read and process the communication between, e.g., residual musculature or brain waves, to transfer them to the executing device and to enable the desired execution.Currently, the greatest amount of evidence exists for the use of exoskeletal systems with different modes of action in the context of gait and stance rehabilitation in paraplegic patients; however, their use also plays a role in the rehabilitation of fractures close to the hip joint and endoprosthetic care. So-called single joint systems are also being tested in the rehabilitation of functionally impaired extremities, e.g., after knee prosthesis implantation. At this point, however, the current data situation is still too limited to be able to make a clear statement about the use of these technologies in the trauma surgery "core business" of rehabilitation after fractures and other joint injuries.For rehabilitation after limb amputation, in addition to the further development of myoelectric prostheses, the current development of "sentient" prostheses is of great interest. The use of 3D printing also plays a role in the production of individualized devices.Due to the current progress of artificial intelligence in all fields, ground-breaking further developments and widespread application possibilities in the rehabilitation of trauma patients are to be expected.

Modeling foot sole cutaneous afferents: FootSim

While walking and maintaining balance, humans rely on cutaneous feedback from the foot sole. Electrophysiological recordings reveal how this tactile feedback is represented in neural afferent populations, but obtaining them is difficult and limited to stationary conditions. We developed the FootSim model, a realistic replication of mechanoreceptor activation in the lower limb. The model simulates neural spiking responses to arbitrary mechanical stimuli from the combined population of all four types of mechanoreceptors innervating the foot sole. It considers specific mechanics of the foot sole skin tissue, and model internal parameters are fitted using human microneurography recording dataset. FootSim can be exploited for neuroscientific insights, to understand the overall afferent activation in dynamic conditions, and for overcoming the limitation of currently available recording techniques. Furthermore, neuroengineers can use the model as a robust in silico tool for neuroprosthetic applications and for designing biomimetic stimulation patterns starting from the simulated afferent neural responses.

Cognitive benefits of using non-invasive compared to implantable neural feedback

A non-optimal prosthesis integration into an amputee’s body schema suggests some important functional and health consequences after lower limb amputation. These include low perception of a prosthesis as a part of the body, experiencing it as heavier than the natural limb, and cognitively exhausting use for users. Invasive approaches, exploiting the surgical implantation of electrodes in residual nerves, improved prosthesis integration by restoring natural and somatotopic sensory feedback in transfemoral amputees. A non-invasive alternative that avoids surgery would reduce costs and shorten certification time, significantly increasing the adoption of such systems. To explore this possibility, we compared results from a non-invasive, electro-cutaneous stimulation system to outcomes observed with the use of implants in above the knee amputees. This non-invasive solution was tested in transfemoral amputees through evaluation of their ability to perceive and recognize touch intensity and locations, or movements of a prosthesis, and its cognitive integration (through dual task performance and perceived prosthesis weight). While this managed to evoke the perception of different locations on the artificial foot, and closures of the leg, it was less performant than invasive solutions. Non-invasive stimulation induced similar improvements in dual motor and cognitive tasks compared to neural feedback. On the other hand, results demonstrate that remapped, evoked sensations are less informative and intuitive than the neural evoked somatotopic sensations. The device therefore fails to improve prosthesis embodiment together with its associated weight perception. This preliminary evaluation meaningfully highlights the drawbacks of non-invasive systems, but also demonstrates benefits when performing multiple tasks at once. Importantly, the improved dual task performance is consistent with invasive devices, taking steps towards the expedited development of a certified device for widespread use.

Optimally-calibrated non-invasive feedback improves amputees' metabolic consumption, balance and walking confidence

OBJECTIVE

Lower-limb amputees suffer from a variety of health problems, including higher metabolic consumption and low mobility. These conditions are linked to the lack of a natural sensory feedback from their prosthetic device, which forces them to adopt compensatory walking strategies that increase fatigue. Recently, both invasive (i.e. requiring a surgery) and non-invasive approaches have been able to provide artificial sensations via neurostimulation, inducing multiple functional and cognitive benefits. Implants helped to improve patient mobility and significantly reduce their metabolic consumption. A wearable, non-invasive alterative that provides similar useful health benefits, would eliminate the surgery related risks and costs thereby increasing the accessibility and the spreading of such neurotechnologies.

APPROACH

Here, we present a non-invasive sensory feedback system exploiting an optimally-calibrated (JND-based) electro-cutaneous stimulation to encode intensity-modulated foot-ground and knee angle information personalized to the user's just noticeable perceptual threshold. This device was holistically evaluated in three transfemoral amputees by examination of metabolic consumption while walking outdoors, walking over different inclinations on a treadmill indoors, and balance maintenance in reaction to unexpected perturbation on a treadmill indoors. We then collected spatio-temporal parameters (i.e. gait dynamic and kinematics), and self-reported prosthesis confidence while the patients were walking with and without the sensory feedback.

MAIN RESULTS

This non-invasive sensory feedback system, encoding different distinctly perceived levels of tactile and knee flexion information, successfully enabled subjects to decrease metabolic consumption while walking and increase prosthesis confidence. Remarkably, more physiological walking strategies and increased stability in response to external perturbations were observed while walking with the sensory feedback.

SIGNIFICANCE

The health benefits observed with the use of this non-invasive device, previously only observed exploiting invasive technologies, takes an important step towards the development of a practical, non-invasive alternative to restoring sensory feedback in leg amputees.

Artificial neuromorphic cognitive skins based on distributed biaxially stretchable elastomeric synaptic transistors

SignificanceEnabling distributed neurologic and cognitive functions in soft deformable devices, such as robotics, wearables, skin prosthetics, bioelectronics, etc., represents a massive leap in their development. The results presented here reveal the device characteristics of the building block, i.e., a stretchable elastomeric synaptic transistor, its characteristics under various levels of biaxial strain, and performances of various stretchy distributed neuromorphic devices. The stretchable neuromorphic array of synaptic transistors and the neuromorphic imaging sensory skin enable platforms to create a wide range of soft devices and systems with implemented neuromorphic and cognitive functions, including artificial cognitive skins, wearable neuromorphic computing, artificial organs, neurorobotics, and skin prosthetics.

Multisensory stimulation decreases phantom limb distortions and is optimally integrated

The multisensory integration of signals from different senses is crucial to develop an unambiguous percept of the environment and our body. Losing a limb causes drastic changes in the body, sometimes causing pain and distorted phantom limb perception. Despite the debate over why these phenomena arise, some researchers suggested that they might be linked to an impairment of multisensory signals inflow and integration. Therefore, reestablishing optimally integrated sensory feedback could be crucial. The related benefits on sensory performance and body self-representation are still to be demonstrated, particularly in lower-limb amputees. We present a multisensory framework combining Virtual reality and electro-cutaneous stimulation that allows the optimal integration of visuo-tactile stimuli in lower-limb amputees even if nonspatially matching. We also showed that this multisensory stimulation allowed faster sensory processing, higher embodiment, and reductions in phantom limb distortions. Our findings support the development of multisensory rehabilitation approaches, restoring a correct body representation.

•

Multisensory platform combining virtual reality and electro-cutaneous stimulation.

•

Leg amputees optimally integrate nonspatially matching visuo-tactile stimulation.

•

Multisensory stimulation allows faster information processing and higher embodiment.

•

Phantom limb distortions are reduced after multisensory stimulation.

A non-invasive wearable sensory leg neuroprosthesis: mechanical, electrical and functional validation

OBJECTIVE

Lower limb amputees suffer from a variety of functional deficits related to the absence of sensory communication between the central nervous system and the lost extremity. Indeed, they experience high risk of falls, asymmetric walking and balance, and low prosthesis embodiment, that significantly decrease their quality of life. Presently, there are no commercially available devices able to provide sensory feedback to leg amputees. Recently, some invasive solutions (i.e. requiring a surgery) have been proposed by different research groups, however a non-invasive effective alternative exploitable in everyday life is still missing.

APPROACH

To address this need we developed and tested a lightweight, non-invasive, wearable technology (NeuroLegs) providing sensory (i.e. knee angle joint and tactile) feedback to the users through electro-cutaneous stimulation. A user-friendly GUI and mobile App have been developed to easily calibrate and control the system. Standard mechanical and electrical tests were performed to assess the safety and reliability of the technology.

MAIN RESULTS

No mechanical failures, stable communication among system parts and a long-lasting battery (>23h) were demonstrated. The NeuroLegs system was then verified in terms of accuracy in measuring relevant gait parameters in healthy participants. A high temporal reliability was found when detecting stride features (important for the real-time configuration) with a correct match to the walking cadence, in all assessed walking conditions. The effectiveness of the NeuroLegs system at improving walking of three transfemoral amputees was then verified in movement laboratory tests. Increased temporal gait symmetry and augmented confidence were found. Stepping outside from the lab, Neurolegs was successfully exploited by a transfemoral amputee in CYBATHLON Global Edition 2020 in several challenging situations related to daily-living activities.

SIGNIFICANCE

Our results demonstrate that the NeuroLegs system provides the user with useful sensory information that can be successfully exploited in different walking conditions of daily life.