Brain–machine interfaces are moving beyond science fiction to clinical reality, offering new hope in stroke recovery, neurodegenerative diseases, and psychiatric disorders. As research advances, therapeutic applications are gaining momentum — but not without profound ethical and regulatory questions.
Introduction: From Sci-Fi to Standard of Care
The idea of interfacing the human brain directly with machines has long fascinated scientists and captivated the public imagination. For decades, brain–machine interfaces (BMIs) were relegated to the realm of speculative fiction, evoking images of mind-controlled computers, robotic limbs, cyborgs like Robocop, and enhanced cognition. In recent years, however, what was once the domain of science fiction has begun to solidify into scientific fact. Advancements in neural engineering, computing power, and miniaturized electronics have transformed BMIs from visionary concepts into viable tools for clinical care.
Historically, BMIs were largely explored through the lens of human enhancement — technologies designed to expand cognitive ability, extend memory, or create immersive brain-controlled experiences. While such applications remain a focus for some developers, especially within the consumer and defense sectors, the momentum has clearly shifted toward therapeutic potential. Increasingly, researchers and clinicians are focused on using BMIs to restore lost function, alleviate symptoms of chronic disease, and offer new treatment modalities for conditions that have been historically difficult to manage, such as paralysis, epilepsy, and severe depression.
This shift in focus is not merely theoretical. Global investment in BMI research and development has surged, supported by a growing ecosystem of academic research labs, medtech startups, and major tech firms. BMI technology was recently named one of the top 10 breakthrough technologies by a leading global innovation review, underscoring its mainstream emergence and expected commercial impact in the coming years.1 Simultaneously, the integration of BMI systems into neurosurgical settings has become increasingly common, particularly for use in functional mapping, deep brain stimulation, and motor rehabilitation.2
As BMI therapeutics continue to mature, they are poised to redefine the interface between the nervous system and medical technology. Here, we explore how these systems work, where they are already making an impact, and what challenges remain on the path from experimental novelty to therapeutic norm.
How BMIs Work: Platforms and Modalities
At their core, BMIs are systems that enable direct communication between the brain and an external device, translating neural activity into actionable commands or using external inputs to modulate brain function. BMIs operate either by recording neural signals to interpret a person’s intent or by delivering stimulation to targeted brain regions to influence neural activity. In some systems, both functionalities are combined, forming closed-loop architectures capable of real-time monitoring and response.
BMI systems are broadly categorized as either invasive or non-invasive, depending on the nature of the connection to the brain. Invasive BMIs involve surgical implantation of electrodes directly into brain tissue or on the cortical surface, offering high spatial and temporal resolution. These systems are frequently used in applications such as deep brain stimulation (DBS), electrocorticography (ECoG), and advanced neuroprosthetics. Non-invasive BMIs, by contrast, typically rely on external sensors, such as electroencephalography (EEG) caps or near-infrared spectroscopy, to capture brain signals without the need for surgery. While less precise, these systems are more accessible and carry lower risk, making them suitable for broader therapeutic deployment.
Another important axis of classification lies in the functional design: recording-based systems aim to decode neural signals for external control (e.g., operating a robotic arm or cursor), while stimulation-based BMIs deliver energy — electrical, magnetic, or optical — to alter brain activity. Increasingly, these two paradigms are being combined in hybrid systems capable of both monitoring and intervention, creating adaptive feedback loops that respond dynamically to the user's neural state.
The underlying technologies powering BMI systems are diverse and rapidly evolving. EEG remains the most widely used non-invasive technique owing to its portability and affordability, though it suffers from low signal resolution. ECoG offers improved resolution and signal fidelity but requires surgical access to the cortical surface. DBS has become a standard-of-care intervention for certain movement disorders, while emerging modalities, such as optogenetics, offer precise control over neural circuits using light. At the cutting edge, nanotechnology is being explored to develop ultra-miniaturized electrodes and injectable sensor arrays.
Recent innovations have focused not only on the physical hardware of BMIs but also on the software needed to interpret and act upon complex neural data. Advances in signal processing, machine learning, and neural decoding have significantly improved BMI performance and reliability. Researchers have developed architectures that incorporate adaptive algorithms capable of learning from and adjusting to individual brain patterns over time.3,4 Artificial intelligence (AI) is playing an increasingly central role in making sense of noisy, high-dimensional brain signals, enabling more accurate and responsive control systems.5,6 These developments are essential for moving BMI systems beyond experimental paradigms and into real-world therapeutic settings, where accuracy, safety, and ease of use are paramount.
Clinical Use Cases and Evidence of Efficacy
As BMI technology evolves, it is transitioning from the laboratory proof-of-concept stage to a clinical tool with demonstrable therapeutic benefits. Across a growing range of neurological and psychiatric conditions, BMIs are being used to restore function, improve quality of life, and offer new treatment modalities where conventional therapies fall short. A growing body of clinical research supports the efficacy of these interventions, particularly in the areas of motor rehabilitation, neurodegenerative disease, and mental health.
One of the most thoroughly studied applications of BMIs is in stroke recovery and motor rehabilitation. Patients who have lost partial or full control of limb movement due to cerebral infarcts or hemorrhages can benefit from BMI systems that detect motor intent from brain activity and translate it into movement through robotic exoskeletons, functional electrical stimulation, or virtual environments. A recent meta-analysis of randomized controlled trials demonstrated that BMI-based therapies significantly improve upper limb motor function in post-stroke patients compared with standard rehabilitation alone.7 These gains are often attributed to enhanced neuroplasticity driven by real-time feedback between motor intention and observable outcomes, reinforcing new neural pathways even in chronically impaired individuals.
Neurodegenerative diseases represent another major frontier for BMI applications. In conditions such as Parkinson’s disease and amyotrophic lateral sclerosis (ALS), the progressive loss of motor function creates severe disability and limits patient independence. Neuroprosthetic BMI systems can bypass damaged neural circuits, allowing patients to regain control over external devices or communicate using brain signals. In Parkinson’s disease, DBS systems have already become a mainstay of treatment for motor symptoms, and next-generation BMIs are being designed to modulate stimulation adaptively based on real-time neural feedback.8 For ALS patients, non-invasive BMIs can provide a crucial communication channel as muscular control deteriorates, preserving autonomy even in advanced stages of the disease.
Mental health and psychiatric disorders are emerging areas of exploration for therapeutic BMIs. While the brain circuits underlying depression, anxiety, and posttraumatic stress disorder (PTSD) are complex and heterogeneous, early clinical data suggest that targeted stimulation of specific brain regions may offer symptom relief for treatment-resistant cases. Research into closed-loop neuromodulation for depression is particularly promising, with systems that adjust stimulation based on biomarkers of mood state showing preliminary efficacy.9 Additionally, BMI applications in psychiatric populations must contend with heightened sensitivity around autonomy and patient identity, prompting careful clinical and ethical design. Studies are also beginning to examine the role of BMI in improving cognitive and emotional regulation in PTSD patients, with some early-phase trials reporting improved mood stability and decreased intrusive thoughts.10
Beyond these headline indications, BMI systems are being investigated for a variety of additional therapeutic uses. In epilepsy, BMIs can detect pre-seizure activity and deliver early warning or responsive stimulation to prevent seizure onset. Chronic pain, particularly when refractory to pharmacological interventions, may also be alleviated through targeted neuromodulation of central pain pathways. In patients with disorders of consciousness — such as coma or minimally conscious states — BMI systems have been used to detect residual cognitive function and, in some cases, facilitate rudimentary communication.2,11
Taken together, these diverse clinical use cases illustrate the broad potential of BMIs to treat conditions that span the neurological and psychiatric spectrum. As more data are gathered and systems are refined, BMI-based therapeutics may become foundational to future standards of care for a wide array of hard-to-treat conditions.
What Counts as a Cure? Ethical Reflections on BMI Reversibility, Permanence, and Patient Expectations
In conventional medicine, “cure” often implies the resolution of disease and a return to baseline function. In the context of BMIs, however, this concept becomes far more complex. Many BMI systems do not cure underlying neurological or psychiatric conditions — they compensate for or work around them, often in ways that require ongoing use. This distinction raises important questions about permanence, reversibility, and patient autonomy.
For implanted devices that deliver chronic stimulation or interpret real-time brain activity, the boundary between user and machine can become blurred over time. Some patients describe the device as an extension of themselves, while others report feelings of dependence or loss of control. If a device is removed or deactivated, is the resulting decline a relapse, or does it mark the withdrawal of a “technological prosthesis” that was never a cure to begin with?
These issues are particularly charged in psychiatric applications, where expectations of mood normalization or personality “correction” may not align with what BMI technologies can safely or ethically provide. For stakeholders — from developers to regulators — the challenge is to balance hope with realism and to design systems that are not only effective but also comprehensible, adjustable, and, when necessary, removable.
Ethical, Psychological, and Societal Implications
The therapeutic promise of BMIs brings with it a set of profound ethical, psychological, and societal challenges that extend beyond technical performance or clinical outcomes. Unlike conventional medical devices, BMIs operate at the interface of cognition, behavior, and identity, raising questions about autonomy, consent, surveillance, and social equity that must be addressed alongside scientific progress.
One of the most frequently cited concerns relates to the preservation of identity and agency. For invasive and closed-loop systems in particular, the capacity of a device to influence neural activity — especially in psychiatric applications — has prompted debate about whether patients remain in full control of their thoughts and emotions. When a BMI adjusts brain function in response to an algorithmic interpretation of mood, for example, it blurs the line between therapeutic intervention and cognitive manipulation. Patients may struggle to distinguish between changes that arise from their own volition and those driven by the device. Ensuring meaningful informed consent in such scenarios is complex, particularly for individuals with impaired decision-making capacity or chronic psychiatric conditions.12
Privacy is another core concern. Because BMI systems record and sometimes transmit sensitive neural data, they open the door to forms of surveillance that were previously unimaginable. The potential misuse of brain data — for marketing, profiling, or coercion — has not gone unnoticed by ethicists and policymakers. These risks are amplified when BMIs are connected to networked devices or integrated into larger digital ecosystems. Maintaining data security and establishing strict limitations on data use will be essential to safeguard user autonomy.
Access and equity present additional challenges. Therapeutic BMIs are currently expensive, technically demanding, and often developed within high-resource settings. As a result, access is likely to be uneven — both within and across national borders — unless intentional policies are implemented to promote affordability and inclusion. At the same time, the prospect of BMI enhancement — using these systems to exceed normal human capacity (think Flowers for Algernon) — raises the possibility of new forms of socioeconomic disparity. If only the wealthy can afford cognitive or emotional augmentation, it may deepen existing inequities or even create new forms of discrimination.
The social acceptability of BMIs also varies by context. In the realm of mental health, stigma already presents barriers to care, and the introduction of BMI-based treatments may be viewed with suspicion or fear, especially when invasive procedures are involved.10,13 Cultural beliefs about the mind, agency, and bodily integrity can strongly influence whether BMI technologies are embraced or rejected. In some communities, there may be discomfort with interventions perceived as unnatural or spiritually invasive. Successful deployment of BMIs will require not only technical adaptation but also cultural sensitivity and community engagement.
As BMI therapeutics continue to advance, these ethical and societal considerations must be treated not as secondary concerns, but as integral components of responsible innovation. The path forward demands a multidisciplinary approach that brings together ethicists, engineers, clinicians, patients, and policymakers to ensure that the development and use of BMIs enhance human well-being without compromising the values that define it.
Regulatory Landscape: Navigating the Gray Zones
The rapid evolution of BMI technologies has outpaced the development of clear regulatory frameworks, leaving innovators and regulators alike navigating a landscape marked by ambiguity and inconsistency. Both the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA) are engaged in ongoing efforts to classify and evaluate BMI devices, but these efforts remain fragmented, particularly when it comes to defining risk categories, establishing clinical endpoints, and determining standards for long-term monitoring and safety.
At present, BMI systems are regulated under existing categories such as medical devices or software-as-a-medical-device (SaMD), depending on their primary function. Invasive BMIs, particularly those that involve implanted electrodes or DBS, are typically subject to rigorous premarket approval processes ownig to their higher risk profiles. These systems are evaluated similarly to other neurosurgical implants, with requirements for biocompatibility, surgical risk mitigation, and detailed clinical evidence. Non-invasive BMIs, such as EEG-based systems, often fall under less restrictive regulatory pathways, especially if their claims are limited to monitoring or communication rather than therapeutic modification.
One of the most persistent regulatory challenges lies in clinical validation. Traditional methods of assessing medical interventions, such as randomized, double-blind trials, are often difficult to apply to BMI systems. For instance, effective blinding can be nearly impossible in studies where patients are directly controlling external devices or receiving noticeable stimulation. Outcome measures are also highly individualized, particularly in neuropsychiatric applications, where symptom relief may be subjective and variable. Establishing standardized, reproducible endpoints remains a key barrier to regulatory confidence and commercial approval.14
Further complicating regulation is the hybrid nature of BMI systems, which combine hardware, software, and biological inputs in ways that challenge traditional oversight structures. Many BMI devices now incorporate adaptive algorithms or machine learning tools that evolve over time in response to patient data. This raises novel questions about how to validate systems that may not perform identically from one patient to the next, or even from one week to the next in the same individual. Regulators must determine not only how to approve such devices initially but also how to monitor them post-market as they continue to learn and adapt.
In response to these emerging challenges, recent recommendations from the U.S. Government Accountability Office (GAO) have called for more proactive and coordinated oversight of neurotechnologies, including BMIs. These recommendations include the development of cross-agency guidance, investment in regulatory science to support novel endpoints, and mechanisms for public engagement on ethical and privacy issues.15 The FDA has also begun to explore new regulatory pathways, such as the Breakthrough Devices Program and Digital Health Software Precertification Pilot, which may be applicable to certain BMI technologies.
Ultimately, the regulatory future of BMI therapeutics will require flexible yet robust frameworks that accommodate both the complexity of the systems and the needs of diverse patient populations. A risk-based, life cycle approach that considers both the invasiveness of the technology and the nature of the intended use may provide a scalable model for oversight. As with the development of the devices themselves, success will depend on sustained dialogue among developers, clinicians, regulators, and patient communities.
Regulatory Snapshot: How the FDA and EMA are Approaching BMI
BMIs straddle multiple regulatory domains, complicating oversight efforts. In the U.S., the FDA categorizes most BMI systems as Class II or III medical devices, depending on their risk level. Invasive systems — such as those involving deep brain stimulation or implanted electrodes — typically require premarket approval, while non-invasive EEG-based devices may qualify for the 510(k) pathway if a predicate device exists. However, many BMI systems incorporate machine learning, adaptive algorithms, or digital therapeutics, raising questions about software validation and post-market surveillance.14
Recent recommendations from the U.S. GAO urge the FDA to work in coordination with other agencies to develop a more coherent oversight model for emerging neurotechnologies, particularly those with behavioral or cognitive implications.15 Suggested actions include clarifying risk classifications, establishing ethical review frameworks, and supporting interdisciplinary research to inform policy.
In Europe, the EMA generally defers BMI device regulation to national competent authorities under the EU Medical Device Regulation (MDR). While similar in principle to the FDA’s risk-based approach, the MDR introduces additional requirements for post-market monitoring, clinical evidence, and cybersecurity — issues of particular relevance for adaptive and networked BMIs.
The takeaway: while both agencies recognize the promise of BMI therapeutics, regulatory clarity remains a work in progress.
Innovation and Industry: Who’s Driving the Future?
The BMI sector is no longer the exclusive domain of academic research or niche medical device companies. A diverse and increasingly competitive innovation ecosystem is taking shape, bringing together Big Tech giants, medtech and biotech firms, academic consortia, and startup accelerators to push BMI technology forward. These players differ in their approaches, priorities, and target markets, but together they are fueling a wave of rapid technological advancement and investment in BMI therapeutics.
Some of the highest-profile efforts are being led by tech companies seeking to pioneer consumer-grade or general-purpose BMI systems. Neuralink, founded with the goal of creating high-bandwidth brain-computer interfaces, has attracted widespread attention for its work on fully implantable systems capable of both reading and writing neural signals, as well as negative attention associated with its animal testing practices. Meta has invested in non-invasive BMI technologies as part of its broader interest in virtual and augmented reality applications, while Synchron has taken a clinically grounded route, advancing minimally invasive endovascular BMIs for motor restoration. These companies bring not only technical resources but also public visibility and investor enthusiasm, helping to normalize BMI development and accelerate timelines.1
Meanwhile, established medtech and biotech companies are focused more squarely on therapeutic outcomes. Firms like Blackrock Neurotech, BrainGate, and Paradromics have built on decades of foundational research to create clinically validated BMI systems aimed at restoring motor function, communication, and autonomy for individuals with severe neurological impairments. These companies often work closely with academic institutions and clinical centers, forming translational partnerships that bridge the gap between early research and real-world deployment. The synergy between academic rigor and industry scalability has proven critical to the successful development of BMI therapeutics.
The BMI startup ecosystem is also expanding, supported by specialized venture funds, incubators, and government grants. New ventures are tackling challenges like wireless signal transmission, miniaturized implantable electronics, biocompatible materials, and real-time neural decoding. However, the path from concept to clinic remains long and uncertain. Translational infrastructure, such as standardized testing platforms, clinical trial networks, and regulatory support, is still underdeveloped in this space, often forcing startups to navigate a complex landscape with limited guidance or precedent.
Intellectual property (IP) is another emerging battleground, especially as BMI technologies become more commercially attractive. Patents around electrode design, neural decoding algorithms, and data integration methods are being filed at a rapid pace, leading to a dense and sometimes overlapping IP landscape. Disputes over ownership and licensing rights may slow innovation or concentrate market power among a few dominant players, particularly as large firms seek to consolidate their positions through acquisitions and strategic partnerships.
Despite the momentum, funding risks remain a persistent challenge. Many BMI ventures require sustained capital over extended development cycles, often with little immediate return. Investor patience can be tested by regulatory delays, technical setbacks, or unclear reimbursement pathways. Companies that fail to balance technical ambition with clinical viability may struggle to maintain support beyond initial proof-of-concept phases.
Nevertheless, the diversity of actors now engaged in BMI innovation reflects the field’s maturation and the growing belief that BMI therapeutics are not just scientifically feasible but commercially and socially impactful. Continued collaboration among academia, industry, and government will be essential to translating promise into practice and ensuring that these technologies serve therapeutic needs rather than remaining confined to technological curiosity.
Toward Patient-Centered Design and Deployment
As BMIs evolve from experimental technologies into viable therapeutic tools, success will increasingly depend on their integration into real-world clinical settings and into the lives of the people who use them. This transition demands a shift in focus from engineering performance alone to holistic, patient-centered design. A therapeutic BMI is not just a piece of hardware or a software algorithm; it is a device that must accommodate the complexities of human behavior, identity, and experience over time.
Engaging patients early in the design and development process is critical. Co-design frameworks that involve users in shaping device features, user interfaces, and feedback mechanisms have shown promise in improving the usability and acceptability of BMI systems. This is especially important in psychiatric applications, where stigmas, vulnerability, and trust play significant roles in treatment decisions. Studies have demonstrated that when patients feel empowered and informed, they are more likely to adopt and adhere to BMI interventions and to participate meaningfully in their refinement.9
However, usability remains a significant barrier to widespread deployment. BMI systems, particularly those used outside of research settings, must be intuitive, comfortable, and responsive. Even minor inconveniences in setup or calibration can discourage use, especially among patients already dealing with complex medical needs. Non-invasive systems require regular signal quality checks and maintenance of sensor interfaces, while implantable devices demand surgical precision, ongoing monitoring, and periodic adjustments to maintain efficacy. Training for both patients and caregivers must be streamlined and accessible, particularly if BMI devices are to be used in home environments or integrated into routine care.
Another challenge is the long-term management of BMI devices. Unlike short-term medical interventions, BMIs often require continuous use and adaptation. Algorithms may need to be updated as a patient’s condition evolves or as new data become available. Hardware components, such as batteries, sensors, or electrodes, may degrade over time, requiring replacements or upgrades. These realities necessitate robust post-implantation care models and raise questions about who bears responsibility for device maintenance and support. If updates are delivered digitally, cybersecurity and data integrity become additional concerns.
Patient neuroethics, an emerging field that explores the subjective experiences of individuals using neural devices, emphasizes that long-term satisfaction with BMI therapy is influenced not only by functional outcomes but also by how the device shapes one’s sense of self and agency. Feelings of being “merged” with or “dependent on” a machine can vary widely across individuals and cultural contexts.16 A truly patient-centered BMI must respect these diverse experiences and provide pathways for patients to express concerns, request modifications, or withdraw from treatment if desired.
As the field moves forward, integrating patient voice into every stage — from preclinical design through long-term follow-up — will be essential to building devices that are not only technologically sophisticated, but also usable, sustainable, and empowering. A future in which BMIs are part of everyday therapeutic practice will require a new standard of responsiveness: not just to neural signals, but to human needs.
Conclusion: Therapeutic Frontier or Pandora’s Box?
BMIs represent one of the most promising and provocative frontiers in modern medicine. With the potential to restore movement, improve cognition, alleviate psychiatric symptoms, and create new pathways for communication, BMI therapeutics offer transformative benefits to patients with conditions that have long resisted conventional treatments. However, this great promise comes with great responsibility. The same technologies that can empower may also intrude; the systems that restore function may challenge identity, autonomy, and privacy in ways no medical device has before.
As BMI development accelerates, the stakes grow higher. A narrow focus on engineering achievements or commercial opportunities risks overlooking the ethical, social, and clinical complexities that determine whether these technologies will be trusted and accepted. Building responsible BMI therapeutics requires sustained collaboration among engineers, clinicians, ethicists, regulators, and, most critically, patients. Each group brings essential perspectives on what it means to safely and meaningfully integrate brain–machine communication into everyday life.
The field has progressed far enough that clinical efficacy is no longer theoretical, yet it remains early enough that norms, standards, and safeguards are still being shaped. Choices made in this phase about regulatory frameworks, data governance, equitable access, and design philosophy will have long-lasting consequences. It is imperative to establish flexible, ethical, and inclusive pathways that allow for innovation while ensuring that BMI technologies serve those who need them most.
The path forward will not be simple, but it is navigable. With foresight, transparency, and a shared commitment to human well-being, BMIs can evolve from a provocative concept into a trusted therapeutic foundation—one that respects not only the intricacies of the brain, but also the dignity of those who live with it.
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