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Neuroprosthetics
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Neuroprosthetics (also called neural prosthetics) is a discipline related to neuroscience and biomedical engineering concerned with developing neural prostheses. They are sometimes contrasted with a brain–computer interface, which connects the brain to a computer rather than a device meant to replace missing biological functionality.[1]

Neural prostheses are a series of devices that can substitute a motor, sensory or cognitive modality that might have been damaged as a result of an injury or a disease. Cochlear implants provide an example of such devices. These devices substitute the functions performed by the eardrum and stapes while simulating the frequency analysis performed in the cochlea. A microphone on an external unit gathers the sound and processes it; the processed signal is then transferred to an implanted unit that stimulates the auditory nerve through a microelectrode array.[2] Through the replacement or augmentation of damaged senses, these devices are intended to improve the quality of life for those with disabilities.

These implantable devices are also commonly used in animal experimentation as a tool to aid neuroscientists in developing a greater understanding of the brain and its functioning. By wirelessly monitoring the brain's electrical signals sent out by electrodes implanted in the subject's brain, the subject can be studied without the device affecting the results. Accurately probing and recording the electrical signals in the brain would help better understand the relationship among a local population of neurons that are responsible for a specific function.[3]

Neural implants are designed to be as small as possible in order to be minimally invasive, particularly in areas surrounding the brain, eyes, or cochlea. These implants typically communicate with their prosthetic counterparts wirelessly. Additionally, power is currently received through wireless power transmission through the skin. The tissue surrounding the implant is usually highly sensitive to temperature rise, meaning that power consumption must be minimal in order to prevent tissue damage.[4]

The neuroprosthetic currently undergoing the most widespread use is the cochlear implant, with over 736,900 in use worldwide as of 2019.[5]

History

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The first known cochlear implant was created in 1957. Other milestones include the first motor prosthesis for foot drop in hemiplegia in 1961, the first auditory brainstem implant in 1977 and a peripheral nerve bridge implanted into the spinal cord of an adult rat in 1981. In 1988, the lumbar anterior root implant and functional electrical stimulation (FES) facilitated standing and walking, respectively, for a group of paraplegics.[6]

Regarding the development of electrodes implanted in the brain, an early difficulty was reliably locating the electrodes, originally done by inserting the electrodes with needles and breaking off the needles at the desired depth.[7] Recent systems utilize more advanced probes, such as those used in deep brain stimulation to alleviate the symptoms of Parkinson's disease. The problem with either approach is that the brain floats free in the skull while the probe does not, and relatively minor impacts, such as a low speed car accident, are potentially damaging. Some researchers, such as Kensall Wise at the University of Michigan, have proposed tethering 'electrodes to be mounted on the exterior surface of the brain' to the inner surface of the skull.[8] However, even if successful, tethering would not resolve the problem in devices meant to be inserted deep into the brain, such as in the case of deep brain stimulation (DBS).

Sensory prosthetics

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Visual prosthetics

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Main article: Visual prosthetic

A visual prosthesis can create a sense of image by electrically stimulating neurons in the visual system. A camera would wirelessly transmit to an implant, the implant would map the image across an array of electrodes. The array of electrodes has to effectively stimulate 600–1000 locations, stimulating these optic neurons in the retina thus will create an image. The stimulation can also be done anywhere along the optic signal's pathway. The optical nerve can be stimulated in order to create an image, or the visual cortex can be stimulated, although clinical tests have proven most successful for retinal implants.

A visual prosthesis system consists of an external (or implantable) imaging system which acquires and processes the video. Power and data will be transmitted to the implant wirelessly by the external unit. The implant uses the received power/data to convert the digital data to an analog output which will be delivered to the nerve via micro electrodes.

Photoreceptors are the specialized neurons that convert photons into electrical signals. They are part of the retina, a multilayer neural structure about 200 μm thick that lines the back of the eye. The processed signal is sent to the brain through the optical nerve. If any part of this pathway is damaged blindness can occur.

Blindness can result from damage to the optical pathway (cornea, aqueous humor, crystalline lens, and vitreous). This can happen as a result of accident or disease. The two most common retinal degenerative diseases that result in blindness secondary to photoreceptor loss is age related macular degeneration (AMD) and retinitis pigmentosa (RP).

The first clinical trial of a permanently implanted retinal prosthesis was a device with a passive microphotodiode array with 3500 elements.[9] This trial was implemented at Optobionics, Inc., in 2000. In 2002, Second Sight Medical Products, Inc. (Sylmar, CA) began a trial with a prototype epiretinal implant with 16 electrodes. The subjects were six individuals with bare light perception secondary to RP. The subjects demonstrated their ability to distinguish between three common objects (plate, cup, and knife) at levels statistically above chance. An active sub retinal device developed by Retina Implant GMbH (Reutlingen, Germany) began clinical trials in 2006. An IC with 1500 microphotodiodes was implanted under the retina. The microphotodiodes serve to modulate current pulses based on the amount of light incident on the photo diode.[10]

The seminal experimental work towards the development of visual prostheses was done by cortical stimulation using a grid of large surface electrodes. In 1968 Giles Brindley implanted an 80 electrode device on the visual cortical surface of a 52-year-old blind woman. As a result of the stimulation the patient was able to see phosphenes in 40 different positions of the visual field.[11] This experiment showed that an implanted electrical stimulator device could restore some degree of vision. Recent efforts in visual cortex prosthesis have evaluated efficacy of visual cortex stimulation in a non-human primate. In this experiment after a training and mapping process the monkey is able to perform the same visual saccade task with both light and electrical stimulation.

The requirements for a high resolution retinal prosthesis should follow from the needs and desires of blind individuals who will benefit from the device. Interactions with these patients indicate that mobility without a cane, face recognition and reading are the main necessary enabling capabilities.[12]

The results and implications of fully functional visual prostheses are exciting. However, the challenges are grave. In order for a good quality image to be mapped in the retina a high number of micro-scale electrode arrays are needed. Also, the image quality is dependent on how much information can be sent over the wireless link. Also this high amount of information must be received and processed by the implant without much power dissipation which can damage the tissue. The size of the implant is also of great concern. Any implant would be preferred to be minimally invasive.[12]

With this new technology, several scientists, including Karen Moxon at Drexel, John Chapin at SUNY, and Miguel Nicolelis at Duke University, started research on the design of a sophisticated visual prosthesis. Other scientists [who?] have disagreed with the focus of their research, arguing that the basic research and design of the densely populated microscopic wire was not sophisticated enough to proceed.

Auditory prosthetics

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Main articles: cochlear implant and auditory brainstem implant

Cochlear implants (CIs), auditory brain stem implants (ABIs), and auditory midbrain implants (AMIs) are the three main categories for auditory prostheses. CI electrode arrays are implanted in the cochlea, ABI electrode arrays stimulate the cochlear nucleus complex in the lower brain stem, and AMIs stimulate auditory neurons in the inferior colliculus. Cochlear implants have been very successful among these three categories. Today the Advanced Bionics Corporation, the Cochlear Corporation and the Med-El Corporation are the major commercial providers of cochlear implants.

In contrast to traditional hearing aids that amplify sound and send it through the external ear, cochlear implants acquire and process the sound and convert it into electrical energy for subsequent delivery to the auditory nerve. The microphone of the CI system receives sound from the external environment and sends it to processor. The processor digitizes the sound and filters it into separate frequency bands that are sent to the appropriate tonotonic region in the cochlea that approximately corresponds to those frequencies.

In 1957, French researchers A. Djourno and C. Eyries, with the help of D. Kayser, provided the first detailed description of directly stimulating the auditory nerve in a human subject.[13] The individuals described hearing chirping sounds during stimulation. In 1972, the first portable cochlear implant system in an adult was implanted at the House Ear Clinic. The U.S. Food and Drug Administration (FDA) formally approved the marketing of the House-3M cochlear implant in November 1984.[14]

Improved performance in cochlear implants not only depends on understanding the physical and biophysical limitations of implant stimulation, but also on an understanding of the brain's pattern processing requirements. Modern signal processing represents the most important speech information while also providing the brain the pattern recognition information that it needs. Pattern recognition in the brain is more effective than algorithmic preprocessing at identifying important features in speech. A combination of engineering, signal processing, biophysics, and cognitive neuroscience was necessary to produce the right balance of technology to maximize the performance of auditory prosthesis.[15]

Cochlear implants have been also used to allow acquiring of spoken language development in congenitally deaf children, with remarkable success in early implantations (before 2–4 years of life have been reached).[16] There have been about 80,000 children implanted worldwide.

The concept of combining simultaneous electric-acoustic stimulation (EAS) for the purposes of better hearing was first described by C. von Ilberg and J. Kiefer, from the Universitätsklinik Frankfurt, Germany, in 1999.[17] That same year the first EAS patient was implanted. Since the early 2000s FDA has been involved in a clinical trial of device termed the "Hybrid" by Cochlear Corporation. This trial is aimed at examining the usefulness of cochlea implantation in patients with residual low-frequency hearing. The "Hybrid" utilizes a shorter electrode than the standard cochlea implant, since the electrode is shorter it stimulates the basil region of the cochlea and hence the high-frequency tonotopic region. In theory these devices would benefit patients with significant low-frequency residual hearing who have lost perception in the speech frequency range and hence have decreased discrimination scores.[18]

For producing sound see Speech synthesis.

Prosthetics for pain relief

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Main article: Spinal Cord Stimulator

The SCS (Spinal Cord Stimulator) device has two main components: an electrode and a generator. The technical goal of SCS for neuropathic pain is to mask the area of a patient's pain with a stimulation induced tingling, known as "paresthesia", because this overlap is necessary (but not sufficient) to achieve pain relief.[19] Paresthesia coverage depends upon which afferent nerves are stimulated. The most easily recruited by a dorsal midline electrode, close to the pial surface of spinal cord, are the large dorsal column afferents, which produce broad paresthesia covering segments caudally.

In ancient times the electrogenic fish was used as a shocker to subside pain. Healers had developed specific and detailed techniques to exploit the generative qualities of the fish to treat various types of pain, including headache. Because of the awkwardness of using a living shock generator, a fair level of skill was required to deliver the therapy to the target for the proper amount of time. (Including keeping the fish alive as long as possible) Electro analgesia was the first deliberate application of electricity. By the nineteenth century, most western physicians were offering their patients electrotherapy delivered by portable generator.[20] In the mid-1960s, however, three things converged to ensure the future of electro stimulation.

  1. Pacemaker technology, which had it start in 1950, became available.
  2. Melzack and Wall published their gate control theory of pain, which proposed that the transmission of pain could be blocked by stimulation of large afferent fibers.[21]
  3. Pioneering physicians became interested in stimulating the nervous system to relieve patients from pain.

The design options for electrodes include their size, shape, arrangement, number, and assignment of contacts and how the electrode is implanted. The design option for the pulse generator includes the power source, target anatomic placement location, current or voltage source, pulse rate, pulse width, and a number of independent channels. Programming options are very numerous (a four-contact electrode offers 50 functional bipolar combinations). The current devices use computerized equipment to find the best options for use. This reprogramming option compensates for postural changes, electrode migration, changes in pain location, and suboptimal electrode placement.[22]

Motor prosthetics

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Devices which support the function of autonomous nervous system include the implant for bladder control. In the somatic nervous system attempts to aid conscious control of movement include Functional electrical stimulation and the lumbar anterior root stimulator.

Bladder control implants

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Main article: Sacral anterior root stimulator

Where a spinal cord lesion leads to paraplegia, patients have difficulty emptying their bladders and this can cause infection. From 1969 onwards Brindley developed the sacral anterior root stimulator, with successful human trials from the early 1980s onwards.[23] This device is implanted over the sacral anterior root ganglia of the spinal cord; controlled by an external transmitter, it delivers intermittent stimulation which improves bladder emptying. It also assists in defecation and enables male patients to have a sustained full erection.

The related procedure of sacral nerve stimulation is for the control of incontinence in able-bodied patients.[24]

Motor prosthetics for conscious control of movement

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Main article: Brain–computer interface

Researchers are currently investigating and building motor neuroprosthetics that will help restore movement and the ability to communicate with the outside world to persons with motor disabilities such as tetraplegia or amyotrophic lateral sclerosis. Research has found that the striatum plays a crucial role in motor sensory learning. This was demonstrated by an experiment in which lab rats' firing rates of the striatum was recorded at higher rates after performing a task consecutively.

To capture electrical signals from the brain, scientists have developed microelectrode arrays smaller than a square centimeter that can be implanted in the skull to record electrical activity, transducing recorded information through a thin cable. After decades of research in monkeys, neuroscientists have been able to decode neuronal signals into movements. Completing the translation, researchers have built interfaces that allow patients to move computer cursors, and they are beginning to build robotic limbs and exoskeletons that patients can control by thinking about movement.[citation needed]

The technology behind motor neuroprostheses is still in its infancy. Investigators and study participants continue to experiment with different ways of using the prostheses. Having a patient think about clenching a fist, for example, produces a different result than having him or her think about tapping a finger. The filters used in the prostheses are also being fine-tuned, and in the future, doctors hope to create an implant capable of transmitting signals from inside the skull wirelessly, as opposed to through a cable.[citation needed]

Prior to these advancements, Philip Kennedy (Emory and Georgia Tech) had an operable if somewhat primitive system which allowed an individual with paralysis to spell words by modulating their brain activity. Kennedy's device used two neurotrophic electrodes: the first was implanted in an intact motor cortical region (e.g. finger representation area) and was used to move a cursor among a group of letters. The second was implanted in a different motor region and was used to indicate the selection.[25]

Developments continue in replacing lost arms with cybernetic replacements by using nerves normally connected to the pectoralis muscles. These arms allow a slightly limited range of motion, and reportedly are slated to feature sensors for detecting pressure and temperature.[26]

Dr. Todd Kuiken at Northwestern University and Rehabilitation Institute of Chicago has developed a method called targeted reinnervation for an amputee to control motorized prosthetic devices and to regain sensory feedback.

In 2002 a Multielectrode array of 100 electrodes, which now forms the sensor part of a Braingate, was implanted directly into the median nerve fibers of scientist Kevin Warwick. The recorded signals were used to control a robot arm developed by Warwick's colleague, Peter Kyberd and was able to mimic the actions of Warwick's own arm.[27] Additionally, a form of sensory feedback was provided via the implant by passing small electrical currents into the nerve. This caused a contraction of the first lumbrical muscle of the hand and it was this movement that was perceived.[27]

In June 2014, Juliano Pinto, a paraplegic athlete, performed the ceremonial first kick at the 2014 FIFA World Cup using a powered exoskeleton with a brain interface.[28] The exoskeleton was developed by the Walk Again Project at the laboratory of Miguel Nicolelis, funded by the government of Brazil.[28] Nicolelis says that feedback from replacement limbs (for example, information about the pressure experienced by a prosthetic foot touching the ground) is necessary for balance.[29] He has found that as long as people can see the limbs being controlled by a brain interface move at the same time as issuing the command to do so, with repeated use the brain will assimilate the externally powered limb and it will start to perceive it (in terms of position awareness and feedback) as part of the body.[29]

Amputation techniques

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The MIT Biomechatronics Group has designed a novel amputation paradigm that enables biological muscles and myoelectric prostheses to interface neurally with high reliability. This surgical paradigm, termed the agonist-antagonist myoneural interface (AMI), provides the user with the ability to sense and control their prosthetic limb as an extension of their own body, rather than using a prosthetic that merely resembles an appendage. In a normal agonist-antagonist muscle pair relationship (e.g. bicep-tricep), when the agonist muscle contracts, the antagonist muscle is stretched, and vice versa, providing one with the knowledge of the position of one's limb without even having to look at it. During a standard amputation, agonist-antagonist muscles (e.g. bicep-tricep) are isolated from each other, preventing the ability to have the dynamic contract-extend mechanism that generates sensory feedback. Therefore, current amputees have no way of feeling the physical environment their prosthetic limb encounters. Moreover, with the current amputation surgery which has been in place for over 200 years, 1/3 patients undergo revision surgeries due to pain in their stumps.

An AMI is composed of two muscles that originally shared an agonist-antagonist relationship. During the amputation surgery, these two muscles are mechanically linked together within the amputated stump.[30] One AMI muscle pair can be created for each joint degree of freedom in a patient in order to establish control and sensation of multiple prosthetic joints. In preliminary testing of this new neural interface, patients with an AMI have demonstrated and reported greater control over the prosthesis. Additionally, more naturally reflexive behavior during stair walking was observed compared to subjects with a traditional amputation.[31] An AMI can also be constructed through the combination of two devascularized muscle grafts. These muscle grafts (or flaps) are spare muscle that is denervated (detached from original nerves) and removed from one part of the body to be re-innervated by severed nerves found in the limb to be amputated.[30] Through the use of regenerated muscle flaps, AMIs can be created for patients with muscle tissue that has experienced extreme atrophy or damage or for patients who are undergoing revision of an amputated limb for reasons such as neuroma pain, bone spurs, etc.

Obstacles

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Mathematical modelling

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Accurate characterization of the nonlinear input/output (I/O) parameters of the normally functioning tissue to be replaced is paramount to designing a prosthetic that mimics normal biologic synaptic signals.[32][33] Mathematical modeling of these signals is a complex task "because of the nonlinear dynamics inherent in the cellular/molecular mechanisms comprising neurons and their synaptic connections".[34][35][36] The output of nearly all brain neurons are dependent on which post-synaptic inputs are active and in what order the inputs are received. (spatial and temporal properties, respectively).[37]

Once the I/O parameters are modeled mathematically, integrated circuits are designed to mimic the normal biologic signals. For the prosthetic to perform like normal tissue, it must process the input signals, a process known as transformation, in the same way as normal tissue.[citation needed]

Size

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Implantable devices must be very small to be implanted directly in the brain, roughly the size of a quarter. One of the example of microimplantable electrode array is the Utah array.[38]

Wireless controlling devices can be mounted outside of the skull and should be smaller than a pager.

Power consumption

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Power consumption drives battery size. Optimization of the implanted circuits reduces power needs. Implanted devices currently need on-board power sources. Once the battery runs out, surgery is needed to replace the unit. Longer battery life correlates to fewer surgeries needed to replace batteries. One option that could be used to recharge implant batteries without surgery or wires is being used in powered toothbrushes.[39] These devices make use of inductive charging to recharge batteries. Another strategy is to convert electromagnetic energy into electrical energy, as in radio-frequency identification tags.

Biocompatibility

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Cognitive prostheses are implanted directly in the brain, so biocompatibility is a very important obstacle to overcome. Materials used in the housing of the device, the electrode material (such as iridium oxide[40]), and electrode insulation must be chosen for long term implantation. Subject to Standards: ISO 14708-3 2008-11-15, Implants for Surgery - Active implantable medical devices Part 3: Implantable neurostimulators.

Crossing the blood–brain barrier can introduce pathogens or other materials that may cause an immune response. The brain has its own immune system that acts differently from the immune system of the rest of the body.[citation needed]

Data transmission

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Wireless Transmission is being developed to allow continuous recording of neuronal signals of individuals in their daily life. This allows physicians and clinicians to capture more data, ensuring that short term events like epileptic seizures can be recorded, allowing better treatment and characterization of neural disease.

A small, light weight device has been developed that allows constant recording of primate brain neurons at Stanford University.[41] This technology also enables neuroscientists to study the brain outside of the controlled environment of a lab.

Methods of data transmission between neural prosthetics and external systems must be robust and secure. Wireless neural implants can have the same cybersecurity vulnerabilities as any other IT system, giving rise to the term neurosecurity. A neurosecurity breach can be considered a violation of medical privacy.

Correct implantation

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Implantation of the device presents many problems. First, the correct presynaptic inputs must be wired to the correct postsynaptic inputs on the device. Secondly, the outputs from the device must be targeted correctly on the desired tissue. Thirdly, the brain must learn how to use the implant. Various studies in brain plasticity suggest that this may be possible through exercises designed with proper motivation.[citation needed]

Technologies involved

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Local field potentials

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Local field potentials (LFPs) are electrophysiological signals that are related to the sum of all dendritic synaptic activity within a volume of tissue. Recent studies suggest goals and expected value are high-level cognitive functions that can be used for neural cognitive prostheses.[42] Also, Rice University scientists have discovered a new method to tune the light-induced vibrations of nanoparticles through slight alterations to the surface to which the particles are attached. According to the university, the discovery could lead to new applications of photonics from molecular sensing to wireless communications. They used ultrafast laser pulses to induce the atoms in gold nanodisks to vibrate.[43]

Automated movable electrical probes

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One hurdle to overcome is the long term implantation of electrodes. If the electrodes are moved by physical shock or the brain moves in relation to electrode position, the electrodes could be recording different nerves. Adjustment to electrodes is necessary to maintain an optimal signal. Individually adjusting multi electrode arrays is a very tedious and time consuming process. Development of automatically adjusting electrodes would mitigate this problem. Anderson's group is currently collaborating with Yu-Chong Tai's lab and the Burdick lab (all at Caltech) to make such a system that uses electrolysis-based actuators to independently adjust electrodes in a chronically implanted array of electrodes.[44]

Imaged guided surgical techniques

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Image-guided surgery is used to precisely position brain implants.[42]

See also

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References

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Further reading

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[edit]
Revisions and contributorsEdit on WikipediaRead on Wikipedia

Neuroprosthetics

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from Grokipedia
Neuroprosthetics are medical devices that interface with the nervous system to restore, substitute, or enhance impaired motor, sensory, or cognitive functions resulting from neurological damage or disease. These devices typically work by recording neural signals, delivering targeted electrical stimulation to neural tissue, or both, thereby bridging disrupted pathways and enabling communication between the brain and external systems or body parts. Common applications include aiding individuals with paralysis, sensory loss, or movement disorders, such as through cochlear implants that restore hearing or deep brain stimulators that alleviate symptoms of Parkinson's disease. Neuroprosthetics can be categorized into sensory, motor, and cognitive types, often overlapping in bidirectional functionality that both senses and stimulates the nervous system. Sensory neuroprosthetics, like cochlear implants—which have been implanted in over 1,000,000 people worldwide as of 2022—or retinal prostheses aimed at vision restoration, target perceptual deficits by converting external stimuli into neural impulses. Motor neuroprosthetics, including functional electrical stimulation systems and brain-computer interfaces (BCIs) such as the BrainGate array with 100 electrodes, facilitate movement control by translating brain signals into actions for prosthetic limbs or cursors, benefiting those with spinal cord injuries or amyotrophic lateral sclerosis. Cognitive variants, though less widespread, support memory or decision-making processes and are under investigation for conditions like epilepsy or neuropsychiatric disorders. The field has evolved since the mid-20th century, with foundational developments including early pacemakers and the first cochlear implants in the 1960s, followed by experiments in 1968 using multi-electrode arrays. Advances in , biomaterials, and have enabled more precise, minimally invasive interfaces, leveraging —the brain's ability to reorganize—for better adaptation and long-term efficacy. Ongoing research focuses on , fully implantable systems and ethical considerations for enhancement beyond restoration, with clinical trials expanding applications to speech decoding and advanced rehabilitation.

Fundamentals

Definition and Principles

Neuroprosthetics are biomedical devices designed to restore or enhance neurological functions impaired by injury, disease, or congenital conditions through direct interfaces with the . These devices employ electrical, optical, or chemical modalities to record neural activity or deliver stimuli, thereby substituting or augmenting lost physiological processes. By bridging the gap between damaged neural pathways and external actuators or sensors, neuroprosthetics enable bidirectional communication that mimics natural neural signaling. At their core, neuroprosthetics operate on principles of neural signal recording and stimulation. Recording involves capturing electrophysiological signals, such as action potentials from individual neurons or local field potentials from neural ensembles, to decode intent or sensory information. Stimulation, conversely, delivers targeted inputs—typically electrical pulses—to evoke neural responses, activating downstream pathways in the brain, spinal cord, or peripheral nerves. This bidirectional exchange facilitates functional restoration, with devices processing raw signals through algorithms to interpret and respond in real time. Neuroprosthetic interfaces vary in invasiveness, each presenting trade-offs between spatial resolution, signal fidelity, and safety. Invasive interfaces, such as penetrating microelectrode arrays (e.g., Utah arrays), achieve high-resolution or stimulation by directly inserting electrodes into neural tissue, but they risk , , and long-term degradation. Semi-invasive options, like (ECoG) grids placed on the brain's surface or epidural stimulators, provide improved stability and reduced tissue penetration compared to fully invasive methods, balancing moderate resolution with lower surgical risks. Non-invasive interfaces, including (EEG) caps or , avoid implantation altogether for enhanced safety and ease of use, though they yield coarser signals due to signal attenuation through scalp and skull. Fundamental components of neuroprosthetic systems include sensors for neural input acquisition, actuators for output delivery, and processors for signal management. Sensors, often electrode arrays, detect and amplify bioelectric signals, while actuators—such as current sources or optical emitters—generate precise stimuli. Central processors employ decoding algorithms to translate recorded activity into commands and encoding strategies to shape stimulation patterns, ensuring adaptive and efficient operation. The effectiveness of electrical stimulation is quantified by the strength-duration relationship, modeled as
I=Irh(1+τt),I = I_{rh} \left(1 + \frac{\tau}{t}\right),
where II is the threshold stimulus current, IrhI_{rh} is the rheobase (minimum current for infinite duration), τ\tau is the chronaxie (duration at twice the rheobase), and tt is the pulse duration; this curve guides parameter selection to minimize energy while achieving reliable neural activation.

Historical Development

The foundations of neuroprosthetics emerged in the late through experiments with , which revealed the electrical nature of nerve and muscle function. In 1786, Italian anatomist observed that electrical discharges could induce contractions in isolated frog legs, demonstrating "animal electricity" as a vital force in biological tissues and sparking interest in electrical stimulation of the . This discovery, building on earlier 18th-century work with , established bioelectricity as a key principle for future neural interfaces, though practical applications remained centuries away. The mid-20th century brought the first implantable neuroprosthetic devices, beginning with cardiac pacemakers. On October 8, 1958, Swedish surgeon Åke Senning implanted the world's first fully implantable pacemaker, developed with engineer , into patient Arne Larsson to treat his complete ; Larsson survived 43 more years, outliving 26 subsequent devices. This success demonstrated the feasibility of chronic electrical stimulation to restore organ function, paving the way for neural applications. Concurrently, sensory neuroprosthetics advanced: in 1957, French electrophysiologist André Djourno and otolaryngologist Charles Eyriès conducted the first , inserting an into the auditory of a deaf patient to elicit sound perceptions via electrical pulses. By the late 1960s, (DBS) was introduced for , with neurosurgeons adapting pacemaker technology to deliver targeted pulses to thalamic and structures, offering relief without destructive lesions. The 1970s and 1980s saw innovations in electrode technology and cortical interfaces, driven by key researchers and institutions. In the early 1970s, biomedical engineer William Dobelle implanted multi-electrode arrays on the of blind volunteers, producing discrete phosphenes—points of light—that formed rudimentary patterns, proving electrical stimulation could bypass damaged eyes to activate vision. The (NIH) bolstered these efforts through its Neural Prosthesis Program, launched in the 1970s, which funded interdisciplinary research into electrode biocompatibility and for motor and sensory restoration. A pivotal advancement came in the 1980s with the Utah Slanted Electrode Array (Utah array), invented by bioengineer Richard Normann at the ; this silicon-based , with up to 100 penetrating shafts, enabled stable, long-term recording and stimulation of individual neurons, becoming a cornerstone for brain-machine interfaces. The 1990s transitioned neuroprosthetics toward integrated brain-computer interfaces (BCIs), with experiments focusing on and cortical restoration. Ophthalmologist Eberhart Zrenner pioneered subretinal prostheses in the early 1990s, implanting microphotodiode arrays beneath the in animal models to convert light into electrical signals, which restored basic visual responses in degenerated and informed human trials. By 1998, neurologist Philip Kennedy achieved a milestone in motor BCIs by implanting a neurotrophic —encapsulated in a neurotrophin-secreting cone—into the of a paralyzed , enabling the individual to control a computer cursor through imagined movements after training. These developments, supported by early initiatives in , laid the groundwork for decoding neural intent to drive prosthetic outputs.

Sensory Neuroprosthetics

Visual Prosthetics

Visual prosthetics, also known as or cortical implants, aim to restore partial vision in individuals blinded by retinal degenerative diseases such as (RP) by electrically stimulating surviving cells in the visual pathway. These devices bypass damaged photoreceptors to activate inner neurons or directly the , eliciting phosphenes—perceived spots of light—that form rudimentary visual percepts. prostheses target the , while cortical ones interface with the brain, offering potential for patients with damage where approaches are ineffective. Retinal prostheses are categorized into epiretinal and subretinal types, both designed to stimulate surviving retinal ganglion cells or bipolar cells. Epiretinal devices, such as the Argus II developed by Second Sight Medical Products, are positioned on the inner surface of the retina and use an external camera-mounted glasses system to capture images, which are processed into electrical signals delivered via a 60-electrode array tethered to an implanted receiver. The Argus II received FDA approval in 2013 under a Humanitarian Device Exemption for adults aged 25 or older with severe to profound RP and bare or no light perception. Production of the Argus II ceased in 2020, and following the company's bankruptcy in 2022, support for external processors ended, impacting device functionality for existing users. Approximately 350 implants were performed worldwide by 2019. In contrast, subretinal prostheses like the Alpha IMS from Retina Implant AG were placed beneath the , integrating a multi-photodiode array of 1,500 electrodes that directly converts incident light into stimulation without relying on external cameras, thus preserving some natural . The Alpha IMS was tested in clinical trials for end-stage RP, demonstrating reliable functionality in restoring limited ; however, development ceased following the dissolution of Retina Implant AG in 2019. Cortical visual prostheses circumvent the entire anterior visual pathway by directly stimulating the primary (V1) with electrode s, making them suitable for cases of atrophy or advanced where implants fail. The Orion system, developed by Cortigent (a of Vivani Medical, formerly Second Sight), features a 60-electrode implanted over the visual cortex, paired with an external headband-mounted camera for image processing and transmission. The early , initiated with the first human implantation in 2018, was completed in 2025, focusing on safety and feasibility in profoundly blind patients. Implantation of retinal prostheses typically involves a procedure, where the vitreous humor is removed to access the , followed by precise positioning of the electrode array using microsurgical tools. For epiretinal devices like Argus II, a tack secures the array to the , while subretinal implants like Alpha IMS required creating a small retinal bleb for placement. Cortical prostheses necessitate a to expose the , allowing subdural or intracortical electrode insertion, often guided by neuronavigation to target V1. These surgeries carry risks such as or hemorrhage but have shown acceptable safety profiles in trials. Clinical outcomes for visual prosthetics include restoration of light perception, motion detection, and basic in controlled environments, though resolution remains low at approximately 20/1260 acuity for Argus II users. Patients with Argus II demonstrated improved orientation and mobility tasks over five years, with benefits persisting in daily activities for RP patients. Alpha IMS trials reported very low vision or low vision recovery, enabling in blind subjects. For patients with damage, cortical options like Orion are more viable. Emerging systems, such as the PRIMA wireless retinal prosthesis developed by Science Corporation, have shown promise for age-related (); in a 2025 , participants regained sufficient vision to read books and navigate obstacles.

Auditory and Other Sensory Prosthetics

Auditory neuroprosthetics primarily target restoration of hearing in individuals with by bypassing damaged cochlear hair cells and directly stimulating the auditory nerve. Cochlear implants consist of an external and that convert into electrical signals, delivered via a surgically implanted multi-channel array inserted into the scala tympani of the . This patterned stimulation mimics natural auditory nerve firing patterns, enabling perception of speech and environmental sounds. A prominent example is the Nucleus device developed by Cochlear Ltd., which has been implanted in over 750,000 users worldwide as of 2025, as part of the broader ecosystem exceeding 1.3 million devices globally. Clinical outcomes demonstrate that 80-90% of post-lingual deaf adults achieve open-set , allowing conversational understanding without lip-reading. For cases where the auditory nerve is damaged, such as in type 2, auditory brainstem implants (ABIs) provide an alternative by directly stimulating the in the . The device features a multi-electrode paddle array placed on the cochlear nucleus surface, activated by an external processor similar to cochlear implants, to evoke auditory sensations. ABIs restore awareness of environmental sounds and limited speech discrimination, though outcomes are generally less robust than cochlear implants due to the more central site. Neuroprosthetics for pain relief, a form of sensory modulation, include spinal cord stimulation (SCS) systems that target chronic by delivering electrical pulses to the dorsal columns of the via implanted multi-channel leads. Approved by the FDA in , these devices interrupt pain signal transmission through the , providing relief in conditions like failed back . Approximately 60% of patients experience at least 50% pain reduction, with sustained benefits in daily function. (VNS), involving an implanted connected to the left , modulates pain associated with by influencing nuclei and descending pain pathways, though its primary FDA approval in 1997 targets refractory seizures. Other sensory neuroprosthetics focus on restoring touch and emerging modalities like olfaction and gustation, often using peripheral nerve interfaces. Haptic feedback in upper-limb prosthetics employs cuff electrodes wrapped around residual sensory nerves to deliver proportional electrical based on grasp force or contact, enabling users to perceive texture and for improved control. Experimental approaches for gustatory restoration include electrotactile stimulation devices that apply patterned currents to the surface, simulating taste sensations via trigeminal and activation, while olfactory interfaces remain in early preclinical stages with direct epithelial to evoke smell perception. These peripheral methods emphasize multi-channel arrays to replicate natural sensory encoding, distinct from central visual approaches.

Motor Neuroprosthetics

Limb and Movement Control Prosthetics

Limb and movement control neuroprosthetics aim to restore voluntary motor function in individuals with paralysis or amputation by interfacing directly with the nervous system to decode intent and actuate prosthetic devices. These systems primarily target skeletal muscle control through central or peripheral neural pathways, enabling users to perform tasks such as grasping objects or navigating environments. Invasive brain-computer interfaces (BCIs) and peripheral nerve techniques represent the core approaches, with clinical trials demonstrating feasibility in restoring functional independence for patients with conditions like spinal cord injury or tetraplegia. Invasive BCIs, such as those employing the Utah array, decode neural signals from the to control external devices like cursors or robotic limbs. The system, utilizing a silicon-based Utah array implanted in the , has been tested in clinical trials since 2004, allowing quadriplegic participants to operate robotic arms and computer interfaces by imagining movements. In one seminal case, participant Matthew Nagle, implanted in 2005, became the first person to control a robotic hand and arm solely through thought, achieving tasks like grasping blocks after just one day of training. trials have shown participants reaching accuracies of up to 86% in two-dimensional cursor control tasks, with some achieving near-real-time performance for point-and-click operations. Integration of BCIs with exoskeletons has further enabled individuals with to perform overground walking, as demonstrated in studies where signals directly modulated lower-limb for natural patterns. Peripheral approaches complement central BCIs by leveraging residual nerves closer to the target muscles, offering less invasive alternatives for amputees. Targeted muscle reinnervation (TMR) surgically redirects severed s to denervated residual muscles, creating new electromyographic (EMG) signal sources for intuitive prosthetic control. Developed in the early 2000s, TMR has been applied in numerous upper-limb amputees, significantly improving myoelectric functionality by mapping specific nerve signals to distinct prosthetic motions, such as elbow flexion or hand grasp. Nerve cuff electrodes provide another peripheral method, encircling peripheral s to record or stimulate fascicles for bidirectional control in neuroprostheses. These cuffs, implanted around nerves like the or ulnar, have enabled selective activation of motor units in prosthetic limbs, with long-term stability observed in implants lasting 2–11 years without significant signal degradation. Key examples illustrate the clinical impact of these technologies. The DEKA Arm, also known as the Luke Arm and funded by the , received U.S. clearance in 2014 for hybrid control combining myoelectric and kinematic inputs, allowing amputees to perform complex tasks like eating or tool use with multiple . systems, applied peripherally, have restored hand grasp in patients by delivering timed pulses to muscles, enabling repetitive functional movements and improving upper-limb motor scores in rehabilitation protocols. TMR-enhanced prosthetics have been shown to increase control intuitiveness, with users reporting reduced and faster task completion compared to traditional myoelectric devices. Overall, these advancements have enabled sustained daily use, with BCI and peripheral systems enabling effective reach-and-grasp tasks in controlled settings. Recent clinical trials, such as the first human implantation of Neuralink's brain-computer interface in 2024, have demonstrated potential for enhanced in patients through high-channel wireless BCIs.

Organ and Internal Control Prosthetics

Organ and internal control prosthetics represent a subset of neuroprosthetics designed to interface with subcortical structures and the to manage involuntary functions and , such as those affecting bladder control, respiration, and neurological conditions like . These devices typically involve implantable electrodes that deliver electrical stimulation to targeted neural pathways, restoring or modulating physiological processes disrupted by injury or disease. Unlike peripheral motor prosthetics, which focus on voluntary limb movement, these systems address deep-seated regulatory mechanisms, often requiring precise implantation in the central or to achieve therapeutic outcomes. Deep brain stimulation (DBS) is a cornerstone of internal control neuroprosthetics, particularly for . In , DBS targets the subthalamic nucleus to alleviate motor symptoms, with the U.S. (FDA) approving bilateral thalamic stimulation for associated tremors in 1997, followed by broader approval for Parkinson's in 2002. Clinical studies demonstrate that DBS can reduce tremors by approximately 70% in responsive patients, alongside improvements in rigidity and bradykinesia, by modulating abnormal neural oscillations in circuits. DBS has also been approved for since 1997 and received humanitarian device exemption for in 2003, where it targets the interna to lessen involuntary muscle contractions, benefiting patients with severe, refractory symptoms. By 2020, over 150,000 DBS implants had been performed worldwide, underscoring its established role in clinical practice. For bladder control in spinal cord injury patients, sacral anterior root stimulators () provide a targeted neuroprosthetic solution by electrically activating the S2-S4 anterior roots to induce detrusor contraction and bladder emptying. Developed in the early , the Vocare Bladder System, an implantable device, received FDA approval in 1998 for individuals with complete lesions above the sacral level. This system, combined with posterior rhizotomy to inhibit reflex dyssynergia, enables voluntary voiding and has achieved continence in approximately 85% of users, significantly reducing reliance on indwelling catheters and associated complications like infections. Long-term data from over 500 early implants show sustained functionality in more than 85% of surviving patients, highlighting its efficacy for restoring autonomic function. Other autonomic neuroprosthetics include stimulators (VNS) and pacers, which address , depression, and . VNS involves implanting electrodes around the left in the neck, connected to a chest ; it gained FDA approval in 1997 as an adjunctive for refractory partial-onset in patients aged 12 and older, reducing frequency by 50% or more in about half of cases through of brainstem nuclei. In 2005, VNS received approval for , where chronic stimulation enhances mood regulation via afferent projections to the and other limbic structures. pacing, meanwhile, stimulates the bilaterally to drive diaphragmatic contraction, serving as an alternative to for ventilator-dependent patients with high cervical injuries or central . Implanted since the 1970s and refined in modern systems, it allows daytime mobility without ventilators, with success rates exceeding 90% in patients with intact , as evidenced by long-term studies of over 40 cases. The mechanisms underlying these prosthetics rely on chronic implantation and programmable stimulation paradigms. Electrodes are surgically placed via stereotactic guidance for or direct nerve cuffing for peripheral systems like SARS and VNS, connected subcutaneously to an implantable (IPG) that delivers adjustable biphasic pulses—typically 1-5 V, 60-130 Hz, and 60-450 μs duration—to mimic or override pathological neural activity. Modern iterations incorporate closed-loop systems, which use onboard sensors to monitor or physiological feedback (e.g., or EEG), dynamically adapting stimulation parameters to optimize efficacy and minimize side effects like or . These adaptive features, validated in preclinical models and early clinical trials, enhance precision by responding to real-time neural states, though widespread adoption remains limited to investigational settings.

Challenges

Technical Challenges

One of the primary technical challenges in neuroprosthetic design is achieving sufficient to minimize tissue disruption while maintaining effective neural interfacing. Current silicon-based arrays, such as the Utah Slant Electrode Array, typically feature diameters of 40–100 µm, which limits the and increases the risk of mechanical mismatch with soft neural tissue. Efforts to scale down to sub-millimeter implants, including reducing diameters to 4–10 µm and decreasing inter-electrode pitch, face hurdles in fabrication precision and signal fidelity, as smaller sizes exacerbate impedance mismatches at the electrode-tissue interface. These constraints necessitate advanced materials like nanoporous or flexible polymers to enable higher-density arrays without compromising long-term stability. Non-rechargeable (DBS) systems typically last 3–5 years (or up to 9 years in some models) before requiring surgical replacement. Rechargeable variants extend battery life to 5–15 years or more but require frequent recharging—often every 1–3 days—posing challenges for patients with motor impairments. inductive charging via near-field coupling addresses these issues by eliminating percutaneous connections, though it introduces efficiency losses of 20–50% due to coil misalignment and tissue absorption. Battery-free alternatives, such as energy-harvesting from or , are emerging but currently yield power densities below 100 µW/cm², insufficient for high-duty-cycle neuroprosthetics. Data transmission in wireless neuroprosthetics is constrained by bandwidth limitations and signal attenuation through biological tissue. High-channel brain-computer interfaces (BCIs) demand data rates of 10–100 Mbps to support simultaneous recording from hundreds of electrodes, yet tissue absorption and reduce effective throughput to 1–10 Mbps . Inductive or ultrasonic methods suffer from exceeding 60 dB/cm in neural tissue, necessitating advanced modulation schemes like to mitigate errors. Compression algorithms are essential to fit raw neural data within these limits, but they risk losing spike timing information critical for decoding. Mathematical modeling of neural signals is essential for decoding intent from noisy recordings, yet computational demands challenge real-time implementation on low-power implants. Kalman filters, a cornerstone of trajectory prediction in motor neuroprosthetics, estimate kinematic states by recursively updating predictions based on observed neural activity. The state update follows the : xk=Axk−1+wk\mathbf{x}_k = A \mathbf{x}_{k-1} + \mathbf{w}_k where xk\mathbf{x}_k is the state vector (e.g., position and ) at time kk, AA is the transition matrix, and wk\mathbf{w}_k is process noise. This approach outperforms static filters in cursor control tasks, achieving correlation coefficients up to 0.8 with motor cortical spikes, but requires tuning to handle non-stationarities like electrode drift. Spike sorting algorithms, often integrated with Kalman decoding, further complicate processing due to overlapping waveforms in multi-unit recordings. Signal-to-noise ratio (SNR) degradation over time, primarily from gliosis-induced encapsulation, reduces recording quality by 10–20 dB within months of implantation in rigid arrays. Flexible polymer-based electrodes, such as those using or conducting polymers, mitigate this by conforming to tissue movement and lowering inflammatory responses, preserving SNR above 5–10 for over a year. These materials enable sub-50 µm features while distributing mechanical stress, though they introduce trade-offs in electrical conductivity compared to metals.

Biological and Ethical Challenges

One major biological challenge in neuroprosthetics is , where the body's to implanted electrodes often leads to —a reactive glial scarring that encapsulates the device and impedes neural signaling. This foreign-body response typically results in significant signal degradation, with high rates of loss observed within the first year post-implantation due to and tissue remodeling. To mitigate , advanced materials such as poly(3,4-ethylenedioxythiophene) (PEDOT) have been developed, which support neuronal network formation while reducing neuroglial reactivity . Correct implantation poses additional biological risks, requiring sub-millimeter precision to target specific neural structures and avoid off-target effects like unintended . MRI-guided techniques achieve radial errors as low as 0.5 mm on average, enabling accurate placement in deep areas. However, surgical complications include rates of 2-5% and hemorrhage around 3%, which can lead to neurological deficits or device failure if not managed promptly. Ethical challenges in neuroprosthetics center on informed consent, particularly for elective enhancements where patients must fully comprehend long-term risks and benefits, including potential alterations to cognition or autonomy. Privacy concerns arise from the sensitive neural data generated, which could be vulnerable to unauthorized access or misuse, raising questions about data ownership and security in brain-computer interfaces; emerging cybersecurity threats, such as potential hacking of neural data streams, further complicate these issues. Access disparities exacerbate inequities, as implantation procedures often exceed $100,000, limiting availability to affluent populations and widening global health gaps; as of 2025, initiatives are underway to reduce costs and improve accessibility. Long-term biological effects include alterations in neural plasticity, where chronic stimulation can reorganize cortical maps and synaptic connections, potentially enhancing but also risking maladaptive changes. There is also concern for dependency or addiction-like behaviors from repeated stimulation, as seen in some cases where patients develop compulsive urges, complicating ethical oversight. Regulatory frameworks address these issues through stringent requirements, such as the FDA's post-market surveillance for class III neurological devices, which mandates ongoing monitoring of adverse events and long-term outcomes. Debates on cognitive enhancement have intensified since Neuralink's initiation of human trials in 2024, with ongoing implants and studies as of 2025 (e.g., speech decoding trials) continuing to spark concerns over , as bidirectional interfaces could influence without clear boundaries between and augmentation.

Technologies

Neural Interfaces

Neural interfaces serve as the foundational hardware components in neuroprosthetics, enabling the recording and of neural activity through direct interaction with or peripheral tissue. These interfaces typically consist of electrodes or optical elements that detect extracellular electrical signals or deliver targeted stimuli, facilitating bidirectional communication between the and external devices. By capturing signals such as action potentials or , or by modulating neuronal firing via electrical or light-based methods, neural interfaces underpin the functionality of sensory and motor prosthetics alike. A key recording modality involves (LFPs), which represent extracellular measurements of the summed synaptic activity from local neuronal populations. LFPs are typically filtered in the frequency range of 0.1-500 Hz to isolate low-frequency components arising from dendritic and somatic currents, distinguishing them from higher-frequency spiking activity. This population-level signal is particularly valuable for decoding ensemble neural dynamics, as it reflects coordinated activity across multiple neurons without requiring single-unit isolation. Individual action potentials, or spikes, are detected from extracellular recordings using threshold-crossing methods, where a signal exceeding approximately 4 times the standard deviation (σ) of the background noise is classified as a spike to minimize false positives. This approach allows for the identification of single-neuron activity amid noisy environments, providing high essential for precise prosthetic control. Various electrode types support these recordings, including microelectrode arrays such as the Utah array, which features 100 electrodes arranged in a 10x10 grid with silicon shanks penetrating cortical tissue for chronic implantation. For peripheral applications, flexible cuff electrodes encircle without penetration, offering multi-site contacts for stable, long-term recording and stimulation of nerve trunks. Optical interfaces, exemplified by , introduce light-sensitive proteins (opsins) into target neurons via , enabling precise through illumination without physical insertion. These proteins, such as , open ion channels in response to specific wavelengths, allowing millisecond-scale control of neuronal excitability with minimal tissue disruption. Electrical methods vary in configuration: monopolar setups use a single active referenced to a distant ground, producing broader current spread, while bipolar configurations employ adjacent pairs for more localized activation, reducing off-target effects. To prevent tissue damage from electrochemical reactions or excessive current, parameters adhere to limits below 30 μC/cm² per phase, ensuring safe reversible charge injection primarily through capacitive mechanisms in materials like or . Advancements in interface design include automated probes that adjust position post-implantation to optimize signal quality over time, compensating for tissue shifts or . For instance, systems incorporating linear actuators enable precise depth adjustments of microelectrode arrays, maintaining consistent neural contact during chronic use. Emerging hybrid electro-optical interfaces integrate electrical recording with optical stimulation on a single platform, combining the high-density spatial resolution of electrodes with the cell-type specificity of to enhance overall prosthetic performance.

Signal Processing and Implantation Methods

Signal processing in neuroprosthetics involves extracting meaningful features from raw neural signals to enable decoding of and control of prosthetic devices. A key step is feature extraction, where techniques such as transforms are employed to isolate neural spikes from and artifacts in extracellular recordings. -based methods decompose signals into time-frequency components, allowing for effective spike detection and denoising, which is crucial for high-density arrays in brain-computer interfaces (BCIs). For instance, continuous transforms have been shown to outperform traditional thresholding in identifying spike events with minimal distortion, preserving for downstream analysis. Machine learning decoders further interpret these extracted features to classify movement intentions or predict continuous outputs. (LDA) is a widely adopted supervised algorithm for intent classification in motor neuroprosthetics, projecting high-dimensional neural data onto a lower-dimensional space to separate classes like left versus right hand movements. LDA's computational efficiency makes it suitable for real-time applications, achieving classification accuracies above 80% in electrocorticography-based BCIs for lower limb control. More advanced decoders, such as Kalman filters, extend this by modeling temporal dynamics for smoother predictions. Control algorithms build on these decoders to provide adaptive, real-time feedback for prosthetic operation. Adaptive filtering techniques, including the recalibrated feedback intention-trained (ReFIT-KF), adjust decoder parameters based on ongoing neural activity to compensate for signal non-stationarities, enhancing control stability over extended sessions. In prediction for cursor or limb control in BCIs, a is often used:
v=Wr\mathbf{v} = \mathbf{W} \mathbf{r}
where v\mathbf{v} is the predicted vector, W\mathbf{W} is a weight matrix learned from training data, and r\mathbf{r} represents the neural firing rates or features. This approach has demonstrated improved tracking performance in chronic implants, with users achieving self-paced control speeds comparable to natural movement. Implantation methods for neuroprosthetic devices emphasize precision to target specific neural structures while minimizing tissue disruption. Image-guided , fusing preoperative computed tomography (CT) and , enables accurate trajectory planning with submillimeter resolution, reducing errors in placement for . This fusion technique aligns anatomical landmarks across modalities, confirming target localization during burr hole creation and insertion. Robotic assistance further refines this process; the ROSA system, for example, provides frameless stereotaxy for DBS lead implantation, achieving radial errors below 1 mm and often under 0.5 mm through automated path computation and tremor-free manipulation. Minimally invasive approaches expand access to cortical and peripheral sites without full . Endovascular delivery involves navigating electrodes via blood vessels to cortical surfaces, as demonstrated in magnetoelectric implants threaded through jugular veins for BCI applications, offering reduced surgical risk compared to open procedures. For peripheral neuroprosthetics, methods insert leads through small skin punctures, targeting nerves like the vagus or for , with implantation times under 30 minutes and complication rates below 5%. During implantation, intraoperative mapping with microelectrode recording (MER) verifies electrode positioning by capturing single-unit activity to delineate functional boundaries, such as in the subthalamic nucleus for DBS. MER trajectories are adjusted in real-time based on characteristic firing patterns, improving targeting accuracy by up to 20%. Postoperatively, device programming for DBS typically involves 4-6 sessions over the first few months, iteratively tuning stimulation parameters like voltage and pulse width to optimize therapeutic effects while mitigating side effects.

Advances and Future Directions

Current Clinical Applications

Neuroprosthetics have established a significant presence in clinical practice, with several FDA-approved devices addressing sensory, motor, and neurological disorders. Cochlear implants, which restore hearing in patients with severe-to-profound , have been implanted in over 1 million individuals worldwide as of recent estimates, enabling improved and . (DBS) systems, primarily used for to alleviate motor symptoms like tremors and rigidity, account for the majority of approximately 263,000 DBS implants globally, with ongoing advancements such as adaptive DBS approved in 2025 for more precise symptom control. stimulation (SCS) devices treat conditions, including failed back surgery syndrome, with around 50,000 new implants annually worldwide, cumulatively benefiting millions of patients through neuromodulation of pain pathways. (VNS) implants, approved for , , and stroke rehabilitation, exceeded 100,000 devices implanted by 2013 and have grown to over 125,000 worldwide as of 2025 across indications. Brain-computer interfaces (BCIs) represent an expanding frontier in clinical applications, particularly for restoring communication in paralyzed patients. In speech restoration, investigational BCIs in NIH-supported trials have achieved decoding rates of up to 62 words per minute for individuals with (ALS) or stroke, allowing real-time synthesis of intended speech from neural signals. Myoelectric prosthetic arms, which use surface to control upper-limb prosthetics for amputees, are widely adopted in clinical settings, particularly in where they serve as standard care for enhancing functional independence in daily activities. A notable example is Neuralink's first human implant in January 2024 for a patient with quadriplegia due to , enabling cursor control and basic digital interaction via thought. The global neuroprosthetics market reached approximately USD 14.1 billion in 2025, fueled by rising incidences of neurological disorders, an aging population, and expanded indications for therapies. Patient outcomes underscore the clinical impact: around 80% of users report high satisfaction with auditory rehabilitation and overall device utility, often citing enhanced . For BCI users with , these systems facilitate independent living by restoring communication autonomy, with studies showing sustained home use improving metrics such as daily interaction and emotional well-being.

Emerging Research and Innovations

Recent advancements in brain-computer interfaces (BCIs) have focused on high-density electrode arrays to enhance signal resolution for motor and sensory restoration. Neuralink's implant features flexible threads with 1024 electrodes, enabling precise neural recording and , and as of 2025, human trials are investigating its application for restoring motor function in individuals with quadriplegia and planning expansions to speech impairments. Complementing invasive approaches, non-invasive alternatives such as functional MRI (fMRI)-guided (TMS) integrated with are emerging for bidirectional communication neuroprosthetics, allowing targeted neural modulation without surgery. Innovations in speech and communication neuroprosthetics emphasize real-time decoding of neural activity into text or synthesized speech. A 2025 UC Berkeley and UC San Francisco collaboration developed a brain-to-voice neuroprosthesis that streams neural signals from the motor cortex, achieving decoding speeds of 47.5 words per minute with near-real-time latency under 1 second and high accuracy for naturalistic speech in paralyzed individuals. Regenerative approaches are advancing through optogenetic prosthetics that combine with light-sensitive proteins to restore neural function. These therapies deliver genes via adeno-associated viruses to surviving or neural cells, enabling light-activated responses for vision restoration in degenerative conditions, with clinical trials demonstrating meaningful visual improvements in patients. Additionally, nanomaterial electrodes, such as graphene-based arrays, improve long-term stability by reducing tissue and maintaining over years, addressing chronic implantation challenges in deep brain interfaces. The integration of , particularly , is enabling adaptive closed-loop systems in neuroprosthetics for dynamic control. These systems use real-time neural feedback to optimize stimulation parameters, as demonstrated in for , where algorithms suppress seizures by adjusting interventions based on ongoing brain states. The Defense Advanced Research Projects Agency's Next-Generation Nonsurgical Neurotechnology (N³) program, active throughout the 2020s, has driven non-surgical neural interfaces using for temporary, reversible brain-machine connections, aiming for 16-channel read/write capabilities without invasion. These developments signal robust growth in the field, with the global neuroprosthetics market projected to reach $62.98 billion by 2034, fueled by innovations in BCIs and regenerative technologies.

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