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

Tactile edges and motion via patterned microstimulation of the human somatosensory cortex

Intracortical microstimulation (ICMS) of somatosensory cortex evokes tactile sensations whose properties can be systematically manipulated by varying stimulation parameters. However, ICMS currently provides an imperfect sense of touch, limiting manual dexterity and tactile experience. Leveraging our understanding of how tactile features are encoded in the primary somatosensory cortex (S1), we sought to inform individuals with paralysis about local geometry and apparent motion of objects on their skin. We simultaneously delivered ICMS through electrodes with spatially patterned projected fields (PFs), evoking sensations of edges. We then created complex PFs that encode arbitrary tactile shapes and skin indentation patterns. By delivering spatiotemporally patterned ICMS, we evoked sensation of motion across the skin, the speed and direction of which could be controlled. Thus, we improved individuals' tactile experience and use of brain-controlled bionic hands.

Clinical trials for implantable neural prostheses: understanding the ethical and technical requirements

Neuroprosthetics research has entered a stage in which animal models and proof-of-concept studies are translated into clinical applications, often combining implants with artificial intelligence techniques. This new phase raises the question of how clinical trials should be designed to scientifically and ethically address the unique features of neural prostheses. Neural prostheses are complex cyberbiological devices able to acquire and process data; hence, their assessment is not reducible to only third-party safety and efficacy evaluations as in pharmacological research. In addition, assessment of neural prostheses requires a causal understanding of their mechanisms, and scrutiny of their information security and legal liability standards. Some neural prostheses affect not only human behaviour, but also psychological faculties such as consciousness, cognition, and affective states. In this Viewpoint, we argue that the technological novelty of neural prostheses could generate challenges for technology assessment, clinical validation, and research ethics oversight. To this end, we identify a set of methodological and research ethics challenges specific to this medical technology innovation. We provide insights into relevant ethical guidelines and assess whether oversight mechanisms are well equipped to ensure adequate clinical and ethical use. Finally, we outline patient-centred research ethics requirements for clinical trials involving implantable neural prostheses.

Wearable non-invasive neuroprosthesis for targeted sensory restoration in neuropathy

Peripheral neuropathy (PN), the most common complication of diabetes, leads to sensory loss and associated health issues as pain and increased fall risk. However, present treatments do not counteract sensory loss, but only partially manage its consequences. Electrical neural stimulation holds promise to restore sensations, but its efficacy and benefits in PN damaged nerves are yet unknown. We designed a wearable sensory neuroprosthesis (NeuroStep) providing targeted neurostimulation of the undamaged nerve portion and assessed its functionality in 14 PN participants. Our system partially restored lost sensations in all participants through a purposely calibrated neurostimulation, despite PN nerves being less sensitive than healthy nerves (N = 22). Participants improved cadence and functional gait and reported a decrease of neuropathic pain after one day. Restored sensations activated cortical patterns resembling naturally located foot sensations. NeuroStep restores real-time intuitive sensations in PN participants, holding potential to enhance functional and health outcomes while advancing effective non-invasive neuromodulation.

Hypersensitive meta-crack strain sensor for real-time biomedical monitoring

Real-time monitoring of infinitesimal deformations on complex morphologies is essential for precision biomechanical engineering. While flexible strain sensors facilitate real-time monitoring with shape-adaptive properties, their sensitivity is generally lower than spectroscopic imaging methods. Crack-based strain sensors achieve enhanced sensitivity with gauge factors (GFs) exceeding 30,000; however, such GFs are only attainable at large strains exceeding several percent and decline below 10 for strains under 10-3, rendering them inadequate for minute deformations. Here, we introduce hypersensitive and flexible "meta-crack" sensors detecting infinitesimal strains through previously undiscovered crack-opening mechanisms. These sensors achieve remarkable GFs surpassing 1000 at strains of 10-4 on substrates with a Poisson's ratio of -0.9. The crack orientation-independent gap-widening behavior elucidates the origin of hypersensitivity, corroborated by simplified models and finite element analysis. Additionally, parallel mechanical circuits of meta-cracks effectively address the trade-off between resolution and maximum sensing threshold. In vivo real-time monitoring of cerebrovascular dynamics with a strain resolution of 10-5 underscores the hypersensitivity and conformal adaptability of sensors.

A neurocognitive pathway for engineering artificial touch

Artificial haptics has the potential to revolutionize the way we integrate physical and virtual technologies in our daily lives, with implications for teleoperation, motor skill acquisition, rehabilitation, gaming, interpersonal communication, and beyond. Here, we delve into the intricate interplay between the somatosensory system and engineered haptic inputs for perception and action. We critically examine the sensory feedback's fidelity and the cognitive demands of interfacing with these systems. We examine how artificial touch interfaces could be redesigned to better align with human sensory, motor, and cognitive systems, emphasizing the dynamic and context-dependent nature of sensory integration. We consider the various learning processes involved in adapting to artificial haptics, highlighting the need for interfaces that support both explicit and implicit learning mechanisms. We emphasize the need for technologies that are not only physiologically biomimetic but also behaviorally and cognitively congruent with the user, affording a range of alternative solutions to users' needs.

Animals as Architects: Building the Future of Technology-Supported Rehabilitation with Biomimetic Principles

Rehabilitation science has evolved significantly with the integration of technology-supported interventions, offering objective assessments, personalized programs, and real-time feedback for patients. Despite these advances, challenges remain in fully addressing the complexities of human recovery through the rehabilitation process. Over the last few years, there has been a growing interest in the application of biomimetics to inspire technological innovation. This review explores the application of biomimetic principles in rehabilitation technologies, focusing on the use of animal models to help the design of assistive devices such as robotic exoskeletons, prosthetics, and wearable sensors. Animal locomotion studies have, for example, inspired energy-efficient exoskeletons that mimic natural gait, while insights from neural plasticity research in species like zebrafish and axolotls are advancing regenerative medicine and rehabilitation techniques. Sensory systems in animals, such as the lateral line in fish, have also led to the development of wearable sensors that provide real-time feedback for motor learning. By integrating biomimetic approaches, rehabilitation technologies can better adapt to patient needs, ultimately improving functional outcomes. As the field advances, challenges related to translating animal research to human applications, ethical considerations, and technical barriers must be addressed to unlock the full potential of biomimetic rehabilitation.

Patterned electrical brain stimulation by a wireless network of implantable microdevices

Transmitting meaningful information into brain circuits by electronic means is a challenge facing brain-computer interfaces. A key goal is to find an approach to inject spatially structured local current stimuli across swaths of sensory areas of the cortex. Here, we introduce a wireless approach to multipoint patterned electrical microstimulation by a spatially distributed epicortically implanted network of silicon microchips to target specific areas of the cortex. Each sub-millimeter-sized microchip harvests energy from an external radio-frequency source and converts this into biphasic current injected focally into tissue by a pair of integrated microwires. The amplitude, period, and repetition rate of injected current from each chip are controlled across the implant network by implementing a pre-scheduled, collision-free bitmap wireless communication protocol featuring sub-millisecond latency. As a proof-of-concept technology demonstration, a network of 30 wireless stimulators was chronically implanted into motor and sensory areas of the cortex in a freely moving rat for three months. We explored the effects of patterned intracortical electrical stimulation on trained animal behavior at average RF powers well below regulatory safety limits.

Clinical Applications and Future Translation of Somatosensory Neuroprostheses

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

Sensory integration for neuroprostheses: from functional benefits to neural correlates

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

Closing the sensory feedback loop is necessary for effective neurorehabilitation

Recent advances in neurotechnology enable somatosensory feedback restoration in disabled individuals. This Perspective discusses how closing the sensory feedback loop with brain implants and nerve electrodes for stimulation may improve rehabilitation and assistive systems for patients.

Organ Neuroprosthetics: Connecting Transplanted and Artificial Organs with the Nervous System

Implantable neural interfaces with the central and peripheral nervous systems are currently used to restore sensory, motor, and cognitive functions in disabled people with very promising results. They have also been used to modulate autonomic activities to treat diseases such as diabetes or hypertension. Here, this study proposes to extend the use of these technologies to (re-)establish the connection between new (transplanted or artificial) organs and the nervous system in order to increase the long-term efficacy and the effective biointegration of these solutions. In this perspective paper, some clinically relevant applications of this approach are briefly described. Then, the choices that neural engineers must implement about the type, implantation location, and closed-loop control algorithms to successfully realize this approach are highlighted. It is believed that these new "organ neuroprostheses" are going to become more and more valuable and very effective solutions in the years to come.

Human somatosensory systems based on sensor-memory-integrated technology

As a representative artificial neural network (ANN) for incorporating sensing functions and memory functions into one system to achieve highly miniaturized and highly integrated devices or systems, artificial sensory systems (ASSs) can have a far-reaching influence on precise instrumentation, sensing, and automation engineering. Artificial sensory systems have enjoyed considerable progress in recent years, from low degree integrations to highly advanced sophisticated integrations, from single-modal perceptions to multimode-fused perceptions. However, there are issues around the large hardware area, power consumption, and communication bandwidth needed during the processes where multimodal sensing signals are converted into a digital mode before they can be processed by a digital processor. Therefore, deepening the research into sensory integration is of great importance. In this review, we briefly introduce fundamental knowledge about the memristor mechanism, describe some representative human somatosensory systems, and elucidate the relationship between the properties of memristor devices and the structure. The electronic character of the sensors, future prospects, and key challenges surrounding sensor-memory integrated technologies are also discussed.

High-frequency amplitude-modulated sinusoidal stimulation induces desynchronized yet controllable neural firing

Regaining sensory feedback is pivotal for people living with limb amputation. Electrical stimulation of sensory fibers in peripheral nerves has been shown to restore focal percepts in the missing limb. However, conventional rectangular current pulses induce sensations often described as unnatural. This is likely due to the synchronous and periodic nature of activity evoked by these pulses. Here we introduce a fast-oscillating amplitude-modulated sinusoidal (FAMS) stimulation waveform that desynchronizes evoked neural activity. We used a computational model to show that sinusoidal waveforms evoke asynchronous and irregular firing and that firing patterns are frequency dependent. We designed the FAMS waveform to leverage both low- and high-frequency effects and found that membrane non-linearities enhance neuron-specific differences when exposed to FAMS. We implemented this waveform in a feline model of peripheral nerve stimulation and demonstrated that FAMS-evoked activity is more asynchronous than activity evoked by rectangular pulses, while being easily controllable with simple stimulation parameters. These results represent an important step towards biomimetic stimulation strategies useful for clinical applications to restore sensory feedback.