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• Agency and responsibility over virtual movements controlled through different paradigms of brain–computer interface
  Agency is the attribution of an action to the self and is a prerequisite for experiencing responsibility over its consequences. Here we investigated agency and responsibility by studying the control of movements of an embodied avatar, via brain computer interf…
  preprints 2019 置信度 0.74
• Can the occipital alpha-phase speed up visual detection through a real-time EEG-based brain-computer interface (BCI)?
  ABSTRACT Electrical brain oscillations reflect fluctuations in neural excitability. Fluctuations in the alpha band (α, 8-12 Hz) in the occipito-parietal cortex are thought to regulate sensory responses, leading to cyclic variations in visual perception. Inspir…
  preprints 2020 置信度 0.74
• Silicon Valley new focus on brain computer interface: hype or hope for new applications?
  In the last year there has been increasing interest and investment into developing devices to interact with the central nervous system, in particular developing a robust brain-computer interface (BCI). In this article, we review the most recent research advanc…
  preprints 2018 置信度 0.74
• Embodiment is related to better performance on an immersive brain computer interface in head-mounted virtual reality: A pilot study
  Brain computer interfaces (BCI) can be used to provide individuals with neurofeedback of their own brain activity and train them to learn how to control their brain activity. Neurofeedback-based BCIs used for motor rehabilitation aim to ‘close the loop’ betwee…
  preprints 2019 置信度 0.74
• Developing a 3- to 6-state EEG-based brain-computer interface for a robotic manipulator control
  Recent developments in BCI techniques have demonstrated high-performance control of robotic prosthetic systems primarily via invasive methods. In this work we develop an electroencephalography (EEG) based noninvasive BCI system that can be used for a similar, …
  preprints 2017 置信度 0.74
• Electrolytic-microbubble dynamics delineate safety thresholds during intracortical microstimulation with flexible neural interfaces
  Intracortical microstimulation (ICMS) with ultraflexible neural electrodes enables low-threshold, chronically stable, and high-resolution modulation of neural circuits, providing a promising strategy for sensory restoration and closed-loop neuromodulation. How…
  europepmc 2026 置信度 0.80
• Reconstruction of Somatic Motor and Sensory Functions in SCI Rats Using a Micro-Electronic Neural Bridge and a B-S-C-S Bidirectional Interface
  Abstract Based on an invention patent scheme for functional reconstruction of injured spinal cord nerves proposed in 2004, our research team developed a four-channel Micro-Electronic Neural Bridge (MENB) system integrated with a Micro-Computer Unit (MCU) for n…
  europepmc 2026 置信度 0.80
• PiEEG Server: An Open-Source Real-Time EEG Streaming Platform for AI-Driven Brain-Computer Interfaces
  We present PiEEG Server, an open-source Python-based streaming platform that bridges low-cost PiEEG electroencephalography (EEG) hardware with modern artificial intelligence (AI) and brain-computer interface (BCI) pipelines. Running on a Raspberry Pi or any Bl…
  europepmc 2026 置信度 0.80
• Learning-related population dynamics in right and left dorsal premotor cortex during typing skill acquisition
  Advances in intracortical brain-computer interface (BCI) technology have enabled increasingly sophisticated communication paradigms, including for decoding intended speech and touch typing. However, the methods by which intracortical neural population dynamics…
  pubmed Hashimoto H, Jude JJ, Levi-Aharoni H, Williams ZM 等 2026 置信度 0.82
• Self-regulation of neuronal activity in prefrontal cortex
  Despite our best efforts to stay focused on a task, our arousal waxes and wanes over time. Lower levels of arousal are typically associated with drowsiness, whereas higher levels are often associated with stress. These changes in arousal move us away from idea…
  europepmc 2026 置信度 0.80
• A Decade of cEEGrid: What the Around-the-Ear Array Can and Cannot Measure
  Abstract Objective. cEEGrid, a C-shaped flexible electrode array worn around the ear, has been applied across auditory, cognitive, brain-computer interface, clinical, and sleep applications. We ask what the array can and cannot measure, why, and what separates…
  europepmc 2026 置信度 0.80
• Spatiotemporal Feature-Enhanced Bi-directional Mamba Network for Motor Imagery EEG Decoding
  Abstract The accurate decoding of motor imagery electroencephalography (MI-EEG) signals is critical for brain-computer interface(BCI) applications in motor rehabilitation. However, existing methods often suffer from insufficient spatiotemporal featurefusion, h…
  preprints 2026 置信度 0.74
• A generalizable speech neuroprosthesis
  Intracortical brain-computer interfaces (BCIs) can restore communication to people with vocal tract paralysis by decoding cortical activity during attempted speech into text. State-of-the-art systems pairing neural-to-phoneme decoders with phoneme-to-word lang…
  pubmed Fogg ZM, Card NS, Wairagkar M, Srinivasan A 等 2026 置信度 0.82
• Comparative Analysis of Tri-Polar Concentric Ring and Conventional Electrodes for Overt and Covert Speech
  Brain-Computer Interface (BCI) is a system that enables the human brain to interact with the external environment without using muscles. Electroencephalography (EEG) is a commonly used modality for measuring neural brain activity. However, its low signal-to-no…
  preprints 2026 置信度 0.74
• Inner Speech Classification Using Deep Learning Techniques for EEG-Based Brain-Computer Interfaces
  Abstract Brain Computer Interface (BCI) is a technology that enables direct brain-to-external device communication without the use of muscles. Inner speech refers to the silent process of mentally imagining or "speaking" to oneself without any vocal output, wh…
  preprints 2026 置信度 0.74
• Yawning reveals energy-dynamics mismatch and neural inertia across state transitions
  Yawning is a highly conserved behavior, yet its neural dynamics across arousal state transitions remain poorly understood. Classical reflex models fail to account for the precise timing of yawns during large-scale changes in brain network organization. Here, w…
  preprints 2026 置信度 0.74
• The Dominant Hand-Area Network: Task- Signal Mismatch and the Decoupling of BCI Skill from Global Efficiency in Postural Motor Imagery
  Abstract Rationale: The neurophysiological basis of motor imagery (MI) is foundational to Brain-Computer Interface (BCI) development. While BCI decoding relies on local sensorimotor rhythms (SMRs), MI itself is a large-scale network process. It is an open, and…
  preprints 2026 置信度 0.74
• Investigating sensorimotor beta burst dynamics as a robust biomarker for graded force modulation in humans
  The most prominent signature associated with motor execution and motor imagery is the event-related desynchronisation and synchronisation (ERD/S) in the mu and beta bands (8-30 Hz). In the context of brain-computer interfaces (BCI), this ERD/S signature is hel…
  preprints 2026 置信度 0.74
• Automated robotic control system for EEG-BCI-guided closed-loop TMS
  Brain-state-guided and closed-loop transcranial magnetic stimulation (TMS) protocols have emerged as methods for decreasing the variability and increasing the therapeutic effectiveness of stimulation protocols. However, most existing brain-state-dependent TMS …
  preprints 2026 置信度 0.74
• What percentage of severely impaired stroke survivors retain residual voluntary EMG?
  Back-ground Beneficial rehabilitation interventions for severely impaired stroke patients are limited. Owing to practical constraints in the routine clinical use of electroencephalogram (EEG)-based brain-computer interfaces, this study investigates the feasibi…
  preprints 2026 置信度 0.74
• E-Taste Signal Encoding and Classification via Multi- Attention Residual Networks Using sEMG Streams in Virtual Sensory Systems
  Abstract The purpose of this study was to improve the precision of electronic taste (E-Taste) categorization through the use of surface electromyography (sEMG) data. A multi-attention channel block and residual learning approach, called MACB-ResNet, was develo…
  preprints 2026 置信度 0.74
• Enhancing Cognitive Rehabilitation in Multiple Sclerosis via P300 Brain-Computer Interfaces: A Proof of Concept
  Background: Multiple sclerosis (MS) affects mainly young and middle aged adults and cognitive impairment significantly impacts their quality of life. This study explores the effects of a cognitive rehabilitation therapy using a P300-based brain-computer interf…
  preprints 2026 置信度 0.74
• Equivalent volitional learning emerges through circuit-specific population dynamics in motor cortex and hippocampus
  Learning operates across different brain circuits to associate population activity patterns with desired outcomes, and to enable volitional reactivation of those patterns to control behavior. These circuits differ profoundly in their architecture and dynamical…
  preprints 2026 置信度 0.74
• Linking Embodiment, Simulator Sickness, and EEG Activity During XR–BCI Use: A Single-Participant Case Study
  Background: Subjective experience is increasingly recognised as an important component of brain–computer interface (BCI) performance in extended reality (XR) environments. Although embodiment and simulator sickness are known to influence user experience, their…
  preprints 2026 置信度 0.74
• Threshold-Calibrated Explainable LightGBM for Feature-Level EEG Hand Open–Close Decoding
  Abstract Accurate decoding of hand movement intention from non-invasive electroencephalography (EEG) remains important for assistive brain-computer interface research, but feature-level EEG representations may be vulnerable to repeated samples, overlapping cla…
  preprints 2026 置信度 0.74
• Motor imagery interventions in stroke patients modulate their brain-heart network dynamics
  Background Motor imagery is widely used in post-stroke rehabilitation research, as it is thought to promote neuroplastic mechanisms underlying motor recovery. The characterization of the associated neurophysiological patterns is therefore crucial to improve ou…
  europepmc 2026 置信度 0.80
• Intracortical BCI Performance is Robust to Changes in Attentional Load During Dual-Tasking
  High performance intracortical brain-computer interface (iBCI) control has been demonstrated in research settings, but performance can still vary within and between sessions. One potential source of this variability is the change in attentional load that comes…
  pubmed Canario E, Shearer C, Akcakaya M, Weber D 等 2026 置信度 0.82
• Decoding local and global fNIRS patterns of kinesthetic and visual-motor imagery in a haptic interface paradigm
  Abstract Motor imagery (MI) involves visual-motor (VMI) or kinesthetic-motor (KMI) perspective-taking. However, there is limited knowledge of the accuracy of identifying the subject's perspective during MI using brain activity patterns. The aim of this study i…
  preprints 2026 置信度 0.74
• Preserved Embedding of Neural Population Activity for Brain Computer Interfaces
  Inferring neural population dynamics from motor cortex recordings is essential for brain-computer interface (BCI) control. However, neural activity patterns during similar behaviors exhibit systematic variability across recording sessions, subjects, and task c…
  preprints 2026 置信度 0.74
• A Comb-Shaped, Silicone-Scaffolded Hydrogel Electrode for Stable Overnight EEG Acquisition in Assistive BCI Applications
  Abstract For older adults with disabilities and aphasia, timely care remains challenging, particularly during the 8-h nocturnal period, creating a need for stable non-invasive EEG interfaces for assistive brain-computer interface (BCI) applications. Asynchrono…
  preprints 2026 置信度 0.74
• Comparison of Point-and-Click Performance Between the Brainfingers BCI and the Mouse
  This study quantitatively evaluates the performance of a non-invasive hybrid brain–computer interface (BCI) compared to a conventional mouse in pointing (point-and-click) tasks. A commercial wearable BCI (Brainfingers), based on electromyography (EMG) and elec…
  preprints 2026 置信度 0.74
• From Thought to Speech: Integrating a Low-Cost Electroencephalography Device with AI to Decode Neural Language Signals in Amyotrophic Lateral Sclerosis Patients
  Purpose Nearly all amyotrophic lateral sclerosis (ALS) patients develop dysarthria, with many progressing to anarthria and global expressive communication failure despite preserved consciousness. Despite the severity of this communication loss, available augme…
  preprints 2026 置信度 0.74
• Cross-task, explainable, and real-time decoding of human emotion states by integrating grey and white matter intracranial neural activity
  Decoding human emotion states from intracranial neural activity is key in developing brain-computer interfaces and new therapies for affective disorders. However, real-world application of decoding requires high performance that integrates neural activity from…
  europepmc 2025 置信度 0.80
• Deep Learning Reveals Cross-Modal Neural Representations of Auditory and Visual Mental Imagery in MEG
  Mental imagery provides a unique window into the brain’s ability to internally simulate sensory experiences, offering valuable insights for both cognitive neuroscience and brain–computer interface (BCI) research. This study examined the neural representations …
  preprints 2026 置信度 0.74
• Dual-Stage Prototype Representation for Robust Cross-Subject Motor Imagery EEG Decoding
  Abstract Motor imagery (MI) electroencephalography (EEG) decoding remains challenging due to severe cross-subject variability and signal non-stationarity, which significantly degrade model generalization to unseen subjects. Existing prototype-based and domain …
  preprints 2026 置信度 0.74
• Multimodal EEG-fNIRS Fusion for Passive BCI-based Depressive State Classification
  Traditional psychiatric assessments for depression are often hindered by subjective bias and patient recall in-accuracy. This paper presents a multimodal passive Brain-Computer Interface (pBCI) designed for the objective screening of depressive traits through …
  preprints 2026 置信度 0.74
• FB-ACMCSP: A Filter-Bank Adaptive Multi-Class Common Spatial Pattern Framework for Cross-Subject Motor Imagery EEG Classification
  Abstract Inter-subject variability remains the principal challenge for zero-calibration brain-computer interface (BCI) deployment, where motor imagery (MI) EEG classifiers must generalize to completely unseen users without individual calibration. Existing Comm…
  preprints 2026 置信度 0.74
• SONIC: A Benchmarking Paradigm for Brain-Computer Interfaces
  Abstract Brain-computer interfaces (BCIs) can restore function for individuals with neuro-logical disorders and have the potential to transform the way people interact with digital systems. However, the development of advanced BCI applications, such as fluent …
  europepmc Sean M. Perkins, Michael Trumpis, Michael E. Reitman, Beata Jarosiewicz 等 2025 置信度 0.80 BenchmarkingComputer scienceBrain–computer interfaceArtificial neural networkInterface (matter)
• Combining ultra-flexible electrodes with two-photon imaging to illuminate brain-wide neural dynamics
  Abstract Brain activity consists of neural signals dynamically coordinated across spatial and temporal scales. To sample distributed brain-wide activity, we combine chronically implanted ultra-flexible electrodes for subcortical recordings with simultaneous tw…
  preprints 2026 置信度 0.74
• Real-Time BCI-Generated Ethnic-Inspired Music Based on Orff Principles: Effects on Relaxation and Potential Support for Language Development in Children with Autism Spectrum Disorder
  Abstract This study presents a real-time brain-computer interface (BCI) framework for generating culturally resonant music from neural oscillations, tailored for potential therapeutic applications in children with autism spectrum disorder (ASD). An optimized e…
  preprints 2026 置信度 0.74
• FB-RCSP-RA: A Filter-Bank Regularized Common Spatial Pattern Framework with Per-Band Riemannian Alignment for Cross-Subject Motor Imagery EEG Decoding
  Abstract Cross-subject motor imagery (MI) electroencephalography (EEG) decoding remains an open challenge in brain-computer interface (BCI) research, with inter-subject covariance shift being the principal obstacle to zero-calibration deployment. Existing Comm…
  preprints 2026 置信度 0.74
• Functional reorganization of motor cortex connectivity during learning
  Learning new tasks requires the brain to reshape the flow of neural activity, but how these changes arise from dynamic neural connectivity remains unclear. Here, we used two-photon photostimulation and calcium imaging to map learning-related changes in connect…
  preprints 2026 置信度 0.74
• An Implantable Digital Bridge Enables Arm And Hand Movements After Tetraplegia
  Abstract A cervical spinal cord injury disrupts the signals between the brain and the region of the spinal cord that coordinates arm and hand movements, causing paralysis. Here, we engineered a chronically implanted and durable Digital Bridge that reestablishe…
  preprints 2026 置信度 0.74
• Lateralization in Scalp EEG Brain Connectivity During Hand Motor Imagery Can Improve Task Classification for Brain-Computer Interfaces
  Abstract Objective: To evaluate brain connectivity reorganization during motor imagery (MI) tasks and assess the utility of EEG-based networks for MI classification compared to 8-13-Hz power spectrum of selected EEG channels, which are commonly used in MI deco…
  europepmc 2025 置信度 0.80
• Distinct neural modes carry information about grasp force and phase in the sensorimotor cortex
  Humans perform a variety of complex hand movements to manipulate objects, requiring precise control of changing forces. Understanding the role of sensorimotor cortex and the cortical dynamics underlying these actions is crucial for developing interventions tha…
  preprints 2026 置信度 0.74
• A low-cost auditory multi-class brain-computer interface based on pitch, spatial and timbre cues
  P300-based brain-computer interfaces (BCIs) are especially useful for people with illnesses, which prevent them from communicating in a normal way (e.g. brain or spinal cord injury). However, most of the existing P300-based BCI systems use visual stimulation w…
  preprints 2013 置信度 0.74
• Limb state accounts for differences between motor imagery and action in motor cortex
  ABSTRACT The motor cortex is involved not only in movement execution but also in motor imagery, a process leveraged by decoding algorithms for brain-computer interface (BCI) applications in individuals with severe motor impairments. Previous work has shown tha…
  preprints 2026 置信度 0.74
• Low-Cost Shield MicroBCI to Measure EEG with STM32
  The article introduces an accessible pathway into neuroscience using the MicroBCI device, which leverages the STM32 Nucleo-55RG development board as the core platform. MicroBCI enables the STM32 board to function as a brain–computer interface, capable of recor…
  europepmc 2025 置信度 0.80
• Control of cortical population activity with patterned microstimulation
  Closed-loop control of cortical activity is a central goal in systems neuroscience and clinical neuromodulation, but most approaches either rely on detailed circuit models that are unattainable in vivo or on open-loop stimulation tuned by trial and error. Here…
  preprints 2026 置信度 0.74
• β-cell-specific Non-invasive Ultrasound Stimulation to Enhance Insulin Release and Glucose Control in Mice
  Abstracts Diabetes poses a significant global health burden, with complications such as cardiovascular disease, stroke, and kidney failure. While insulin therapy is central to type 2 diabetes (T2D) management, its limitations—including rapid degradation and th…
  preprints 2025 置信度 0.74
• Simulation of Natural Language from Brain Activity Using Wearable EEG and Deep Learning
  Severe motor impairments such as amyotrophic lateral sclerosis and locked-in syndrome lead to partial or complete loss of speech, severely restricting communication as voluntary motor control deteriorates. In this study, we developed a non-invasive, wearable E…
  preprints 2026 置信度 0.74
• Cortical oscillations reflect opponent ensemble dynamics through coordinated multifrequency activity
  Neural oscillations are widely used as proxies for neuronal activity, where power in individual frequency bands is commonly interpreted as functionally indexing neural circuit engagement. However, power in individual frequency bands shows heterogeneous and som…
  preprints 2026 置信度 0.74
• Conceptual Framework for Finite Element Analysis of Brain–Electrode Interactions Using Open-Source Tools
  Abstract The rapid development of brain–computer interface (BCI) technologies has heightened the need for computational tools that optimize neural implant design. Understanding the mechanical interactions between implanted electrodes and brain tissue is critic…
  preprints 2025 置信度 0.74
• Review of EEG Based Taste Classification Methods
  Abstract This review covers the new field of using technology like EEG (brain-wave reading) and BCI (Brain Computer Interface) to objectively classify taste, offering a more reliable alternative to traditional methods. It analyzes studies from 2015 to 2024 det…
  europepmc 2025 置信度 0.80
• Intent Drift in LLM-Assisted Brain Computer Interface Communication: An In-Silico Benchmark Under Simulated Decoder Corruption
  Background Large language models (LLMs) are increasingly used to correct noisy, error-prone text typed through brain-computer interfaces (BCIs) and other assistive communication devices. A fluent correction can still be wrong: the model can substitute a differ…
  europepmc 2026 置信度 0.80
• Aperiodic EEG exponent as a cortical excitation-inhibition index in ALS brain-computer interface users
  Abstract Objective: The aperiodic (1/f) component of the EEG power spectrum indexes the cortical excitation-to-inhibition (E:I) ratio and is predicted to be progressively altered by amyotrophic lateral sclerosis (ALS), a disease defined by cortical hyperexcita…
  europepmc Khanh-Dung Tran 2026 置信度 0.80
• Transcranial magnetic stimulation-based brain-computer interface with neurofeedback facilitates motor imagery of different daily life hand actions
  Abstract Background: Non-invasive brain-computer interfaces (BCIs) in combination with motor imagery (MI) and neurofeedback (NF) enable users to modulate motor-related brain activity without producing actual motor output. While most non-invasive MI-based BCIs …
  europepmc 2026 置信度 0.80
• Review of brain-computer interface technology in ophthalmology: Current status, challenges and future directions.
  Visual impairment is a major global public health issue. Irreversible blindness caused by end-stage outer retinal diseases, optic nerve injuries, and other conditions remains refractory to conventional therapies. Brain-Computer Interface (BCI) technology, whic…
  pubmed Zhou J, Hu D, Wu M, Hong Z 等 2026 置信度 0.82
• Brain–computer interface-assisted pneumatic hand training improves upper limb function after stroke: a randomized controlled trial and EEG characterization
  Abstract Background The clinical efficacy of brain–computer interface (BCI)–based rehabilitation after stroke remains uncertain, particularly in the subacute phase, where evidence is limited and clinically meaningful improvement is seldom evaluated. This study…
  europepmc 2026 置信度 0.80
• Effects of brain-computer interface-based training on post-stroke lower limb rehabilitation: A systematic review and meta-analysis of randomized controlled trials.
  Lower-limb motor dysfunction after stroke severely compromises mobility and quality of life. Brain-computer interface (BCI) technology, which employs a "central-peripheral-central" closed-loop to promote neuroplasticity, offers a promising rehabilitation appro…
  pubmed Liu X, Huang P, Wu L, Cai L 2026 置信度 0.82
• Brain-computer interface clinical trial design considerations and clinical outcome assessments in pivotal studies: a summary of the 11th BCI society meeting 2025 workshop.
  The Brain Computer Interface (BCI) Society Meeting 2025 held a workshop in collaboration with the Implantable BCI Collaborative Community (iBCI-CC) to discuss the selection, development and validation of clinical trial outcome assessments (COAs) for pivotal st…
  pubmed Sawyer A, Welle CG, French J, Kelemen J 等 2026 置信度 0.82
• Brain-computer interface for upper limb functional recovery post-stroke: a meta-analysis of improvement in upper limb motor function and changes in neurophysiological markers.
  Brain-Computer Interface (BCI) has emerged as a promising intervention, facilitating recovery of upper limb motor function, enhancing associated neurophysiological markers, and improving activities of daily living (ADL) performance, which is measured using the…
  pubmed Zhang H, Xian R, Zhang Y, Liu X 等 2026 置信度 0.82
• An Online Brain-Computer Interface for Detecting Incongruity in Augmented Reality Applications
  Abstract Objective Augmented reality can provide digital information about physical entities presented within its real-world context. However, this information might disagree with the user’s expectations due to factual errors in the data or cognitive biases. S…
  europepmc Michael Wimmer, N. ElSayed, Bruce H. Thomas, Gernot R. Müller-Putz 等 2025 置信度 0.80
• Different feedback modes of brain-computer interface training for upper limb motor function after stroke: a protocol for a systematic review and network meta-analysis.
  Upper limb motor impairment after stroke is a major contributor to long-term disability and can have lasting effects on patients' activities of daily living, social participation, and quality of life. Brain-computer interface (BCI) training establishes a close…
  pubmed Li Y, Deng Y, Deng L, Lu X 等 2026 置信度 0.82
• Enabling Adaptive Interaction in the Metaverse Using a Hybrid EEG-Based Brain–Computer Interface
  This paper presents a hybrid model for the control of brain-computer interfaces (BCIs) for Metaverse environments, with the goal of advancing the capabilities of such interfaces beyond the traditional motor imagery (MI) or P300-based brain-computer interfaces.…
  europepmc Sapthak Mohajon Turjya 2026 置信度 0.80
• A wireless subdural-contained brain-computer interface with 65,536 electrodes and 1,024 channels.
  pubmed Jung T, Zeng N, Fabbri JD, Eichler G 等 2025 置信度 0.82
• Sensing Cognitive Responses Through a Non-Invasive Brain-Computer Interface
  The main objective of this study is to investigate the influence of cognitive stress (mental workload) on some physiological parameters and reactions of a set of experimental subjects. The aim is to check whether these indicators, observed simultaneously, can …
  europepmc 2025 置信度 0.80
• Non-Invasive EEG-Based Brain-Computer Interface for Real-Time Prosthetic Hand Control
  Abstract This paper highlights a non-invasive EEG-controlled brain–computer interface BCI system for real-time control over a developed prosthetic hand system. Motor imagery trials involving opening, closing, grasping, and resting states were conducted using a…
  europepmc Maryam Iqbal, Momna Majeed, Zainab Batool, Amna Batool 等 2026 置信度 0.80
• A retrospective analysis of post-stroke rehabilitation with real world use of brain-computer interface.
  The IpsiHand™ System is an FDA-authorized, non-invasive therapy for chronic stroke-induced upper limb motor impairment that uses a brain-computer interface (BCI) to translate intent-to-move signals into hand movement. This retrospective study evaluated real-wo…
  pubmed Neha Prasad, Nikhita Perry, Allison L. Goldring, Lee A. Fleisher 等 2026 置信度 0.82 Minimal clinically important differenceMedicineRehabilitationPhysical therapyPhysical medicine and rehabilitation
• A brain-computer interface working definition.
  europepmc Marc W. Slutzky, Mariska J. Vansteensel, Christian Herff, Robert A. Gaunt 2025 置信度 0.80 Brain–computer interfaceInterface (matter)Computer scienceMedicineHuman–computer interaction
• Engaging Children in Brain-Computer Interface (BCI) Development: Utilizing an Interactive iPad Tool to Capture Picture-Based P300-Based BCI Augmentative and Alternative Communication Design Preferences.
  P300-based brain-computer interface augmentative and alternative communication (P300-BCI-AAC) systems show promise for supporting communication for children with severe speech and physical impairments. However, little is known about how children prefer these d…
  pubmed Pitt KM, Thiessen A, Fowler G, Butler E 2026 置信度 0.82
• The ASME-speller: 30-class auditory brain-computer interface speller using stream segregation and the QWERTY layout.
  Introduction: This study presents the ASME-speller, a novel 30-class auditory brain-computer interface (BCI) speller system that combines auditory stream segregation with the familiar QWERTY keyboard layout to facilitate intuitive and visionfree communication.…
  europepmc Simon Kojima, Shin’ichiro Kanoh 2026 置信度 0.80 Computer scienceSpeech recognitionFocus (optics)PreprocessorInterface (matter)
• Improving motor imagery decoding methods for an EEG-based mobile brain-computer interface in the context of the 2024 Cybathlon.
  BACKGROUND: Brain-computer interfaces (BCIs) have shown significant promise over the past decades, but often fail to meet the requirements for portability and usability in real-world scenarios. Motivated by the Cybathlon 2024 competition, we developed a modula…
  pubmed Tscherniak IW, Thiemann NC, McWhinnie-Fernández A, Curcean I 等 2026 置信度 0.82
• A potential field shared control approach for wheelchair navigation via brain-computer interface.
  pubmed Xia Y, Wei Y, Li S, Mai X 等 2025 置信度 0.82
• Editorial. Defining value and function in miniaturized cortical arrays for human brain-computer interface applications.
  europepmc Ahmad Alhourani, Nader Pouratian 2026 置信度 0.80
• Towards a Brain-Computer Interface (BCI) for Improving Phonological Processing in Developmental Dyslexia: An Exploratory Study
  Abstract Brain-computer interfaces (BCIs) have immense potential regarding the provision of therapies for disorders of development, but to date have typically been created for non-linguistic disorders such as ADHD (attention deficit hyperactivity disorder). He…
  europepmc Xuanci Zheng, João Araújo, Quentin Busson, Usha Goswami 2026 置信度 0.80
• EEG-based brain-computer interface with immersive virtual reality for phantom limb pain: a single-center pilot neurofeedback trial.
  Phantom limb pain (PLP) is a challenging neuropathic pain condition following limb amputation or brachial plexus injury. Non-pharmacological interventions such as motor imagery training, phantom motor execution and mirror therapy have shown potential to allevi…
  pubmed Roualdes V, Moussaoui S, Normand JM, Kuhn E 等 2026 置信度 0.82
• [Review of Progress of Optical Brain-Computer Interface Technology and Prospects for Medical Device Testing Technology].
  pubmed Wang Y, Mi Y, Zhang X, Zhao B 等 2026 置信度 0.82
• Real-time channel selection for enhanced steady-state visual evoked potentials online brain-computer interface systems.
  Background In recent years, researchers have actively developed new brain-computer interface (BCI) systems while seeking optimal channel combinations. Although channel selection has advanced significantly in BCI systems, few studies have specifically addressed…
  europepmc 2026 置信度 0.80
• Feasibility of decoding cerebellar movement-related potentials for brain-computer interface applications.
  Objective. In brain-computer interface (BCI) applications, signals are conventionally acquired from the cerebrum, and only a subset of the complex interactions that occur in several areas of the brain are collected. One area that has not been investigated for …
  pubmed Russo JS, Colebatch JG, Lin CS, John SE 等 2025 置信度 0.82
• Brain-Computer Interface for EEG-Based Authentication: Advancements and Practical Implications.
  Authentication is a critical component of digital security, and traditional methods often encounter significant vulnerabilities and limitations. This study addresses the emerging field of EEG-based authentication systems, highlighting their theoretical advance…
  pubmed Lamia Alahaideb, Abeer Al-Nafjan, Hessah Aljumah, Mashael Aldayel 等 2025 置信度 0.82 Computer scienceSupport vector machineRandom forestAuthentication (law)Electroencephalography
• SSVEP-based brain-computer interface enabling graded dyspnoea self-report: proof-of-concept study in healthy volunteers.
  Background Mechanically ventilated patients may experience respiratory suffering, which is difficult to assess when verbal communication is impaired. We evaluated the performance of a steady-state visual evoked potential (SSVEP)-based brain-computer interface …
  europepmc 2026 置信度 0.80
• A Moment of Reckoning for Implanted Brain-Computer Interface Studies.
  The field of brain-computer interfaces (BCIs) has fascinated scientists, clinicians, engineers, and the public since Jacques Vidal1 coined the term in 1973. Enthusiasm stems from the promise that BCIs might restore lost function, circumvent disability, and she…
  pubmed Kai J. Miller, Aviva Abosch, Miller KJ, Abosch A 2025 置信度 0.82 MedicineBrain–computer interfaceInterface (matter)Moment (physics)Physical medicine and rehabilitation
• IIMCNet: Intra- and Inter-Modality Correlation Network for Hybrid EEG-fNIRS Brain-Computer Interface.
  Hybrid Brain-Computer Interface (BCI) enhances accuracy and reliability by leveraging the complementary information provided by multi-modality signal fusion. EEG-fNIRS, a fusion of electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS), h…
  europepmc 2026 置信度 0.80
• A Decade of Rapid Serial Visual Presentation Paradigm in Brain-Computer Interface for Target Detection: Current Status and Trends.
  OBJECTIVE: Electroencephalography (EEG)-based Rapid Serial Visual Presentation (RSVP) has steadily gained attention since 2015 as a paradigm to enhance image target detection in brain-computer interfaces (BCIs) used with healthy individuals. METHODS: We review…
  pubmed Xu M, Zhang B, Zhang L, Wang D 等 2025-08-29 置信度 0.82 Brain–computer interfacePresentation (obstetrics)Computer scienceInterface (matter)Human–computer interaction
• Noninvasive Graphene Brain-Computer Interface Integrating EEG Recording and Acoustic-Optical Stimulation for Rhythm Intervention.
  Noninvasive wearable stimulation-acquisition integrated brain-computer interfaces (BCIs) have significant application value in neurological rehabilitation and health monitoring. However, their widespread adoption depends on the development of long-term, stable…
  europepmc 2026 置信度 0.80
• Bayesian Signal Matching for Transfer Learning in ERP-Based Brain Computer Interface.
  An Event-Related Potential (ERP)-based Brain-Computer Interface (BCI) Speller System assists people with disabilities to communicate by decoding electroencephalogram (EEG) signals. A P300-ERP embedded in EEG signals arises in response to a rare, but relevant e…
  pubmed Ma T, Huggins JE, Kang J 2026 置信度 0.82
• Exploring Imagined Movement for Brain-Computer Interface Control: An fNIRS and EEG Review.
  Brain-Computer Interfaces (BCIs) offer a non-invasive pathway for restoring motor function, particularly for individuals with limb loss. This review explored the effectiveness of Electroencephalography (EEG) and function Near-Infrared Spectroscopy (fNIRS) in d…
  pubmed Robert Finnis, Adeel Mehmood, Henning Holle, Jamshed Iqbal 等 2025 置信度 0.82 Brain–computer interfaceElectroencephalographyMotor imageryComputer scienceNeuroimaging
• Study on exploring the relationships between physiological indicators in near-death experiences by drawing on in-mold electronics and node displacement concepts in brain-computer interface signal transmission.
  The association between near-death experiences (NDEs) and physiological indicators remains an unsolved mystery, which hinders in-depth understanding of the essence of consciousness and life processes. Traditional single-indicator analysis methods have limitati…
  pubmed Chang H, Li J, Kang D, Long F 等 2026 置信度 0.82
• A multi-dimensional CNN-Bi-GRU for IoT-based brain-computer interface in early epileptic seizure detection.
  Abstract The study focuses on seizure detection using EEG data from Mendeley. An early-alert IoT-BCI system is designed to simulate real-time support for patients during seizures. The proposed Multi-Dimensional CNN-Bi-GRU (MDCBG) outperforms hybrid deep learni…
  pubmed Paneru B, Biplov Paneru 2026 置信度 0.82
• A Brain-Computer Interface for Improving Auditory Attention in Multi-Talker Environments.
  There is significant research in accurately determining the focus of a listener’s attention in a multi-talker environment using auditory attention decoding (AAD) algorithms. These algorithms rely on neural signals to identify the intended speaker, assuming tha…
  europepmc Stephanie Haro, Christine Beauchene, Thomas F. Quatieri, Christopher J. Smalt 2025 置信度 0.80 Computer scienceBrain–computer interfaceDecoding methodsNeurofeedbackSession (web analytics)
• BAMBI: A Ca<sup>2+</sup> imaging-based brain-computer interface for longitudinal neuronal tracking in freely behaving mice.
  Brain-computer interfaces (BCIs) are powerful tools for investigating neuronal dynamics underlying cognitive processes. However, BCIs commonly rely on electrophysiological techniques, which are limited in their ability to track populations of the same neurons …
  pubmed Balilti-Turgeman L, Shalvi N, Pinchasof O, Geva N 等 2026 置信度 0.82
• Sub-scalp EEG for sensorimotor brain-computer interface.
  Objective . To establish sub-scalp electroencephalography (EEG) as a viable option for brain-computer interface (BCI) applications, particularly for chronic use, by demonstrating its effectiveness in recording and classifying sensorimotor neural activity. Appr…
  europepmc 2025 置信度 0.80
• Restoring brain-to-text communication in a person with dysarthria from pontine stroke using an intracortical brain-computer interface
  Abstract Restoring communication for people with dysarthria secondary to pontine stroke remains a critical challenge. Intracortical brain-computer interfaces (iBCIs) have demonstrated great potential for speech restoration in people with amyotrophic lateral sc…
  europepmc Samuel R. Nason, Pranav Deevi, Qinwan Rabbani, Brandon G. Jacques 等 2026 置信度 0.80 DysarthriaBrain–computer interfaceElectrocorticographyLocked-in syndromeStroke (engine)
• Constraint-Driven Causal Representation Learning for Vigilance Robust Estimation in Brain-Computer Interface.
  Vigilance estimation is a critical task within the field of brain-computer interfaces, extensively applied in monitoring and optimizing user states during human-machine interaction using electroencephalography (EEG). However, most existing vigilance prediction…
  europepmc 2025 置信度 0.80
• A Dimensionality Reduction Approach for Motor Imagery Brain-Computer Interface Using Functional Clustering and Graph Signal Processing.
  Background This paper introduces an approach for dimensionality reduction and classification of electroencephalogram signals in motor imagery brain-computer interface (MI-BCI) systems. Materials and methods The proposed Kron-reduced generic learning regulariza…
  europepmc 2026 置信度 0.80
• The effect of perceived auditory feedback on speech Brain-Computer Interface decoding performance.
  Brain-Computer Interfaces (BCI) provide alternative means of communication for individuals with severe motor impairment. Implantable speech BCIs have shown great potential, particularly in individuals who could still produce some speech-related movements and/o…
  pubmed Schippers A, Berezutskaya J, Vansteensel MJ, Freudenburg ZV 等 2025 置信度 0.82
• Brain-Computer Interface Improves Symptoms of Isolated Focal Laryngeal Dystonia: A Single-Blind Study.
  BACKGROUND AND OBJECTIVE: Laryngeal dystonia (LD) is a focal task-specific dystonia, affecting speaking but not whispering or emotional vocalizations. Therapeutic options for LD are limited. We developed and tested a non-invasive, closed-loop, neurofeedback, b…
  pubmed Stefan K. Ehrlich, Garrett Tougas, Jacob Bernstein, Nicole Buie 等 2025-11-07 置信度 0.82 MedicinePathophysiologyNeurological disorderPhysical medicine and rehabilitationNeurofeedback
• Seasickness Alleviation based on a Mindfulness Brain-Computer Interface.
  Seasickness is a common condition that negatively affects both the experience of passengers and the operating performance of maritime personnel. Techniques aimed at redirecting attention have been proposed to alleviate motion sickness symptoms; however, their …
  europepmc 2025 置信度 0.80
• Unlocking Naturalistic Speech With Brain-Computer Interface.
  SUMMARY Novel speech brain‐computer interface poses the ability to decode detected neural signals in nearly real time. This decreases brain‐to‐voice latency and has the opportunity to restore naturalistic communication. Trial Registration: ClinicalTrials.gov :…
  europepmc Aakash M. Shah 2025 置信度 0.80