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• Filter banks guided correlational convolutional neural network for SSVEPs based BCI classification.
  Objective. In the field of steady-state visual evoked potential brain computer interfaces (SSVEP-BCIs) research, convolutional neural networks (CNNs) have gradually been proved to be an effective method. Whereas, majority works apply the frequency domain chara…
  pubmed Wen X, Jia S, Han D, Dong Y 等 2024 Oct 4 置信度 0.82
• A comprehensive survey of evolutionary algorithms and metaheuristics in brain EEG-based applications.
  Electroencephalography (EEG) has emerged as a primary non-invasive and mobile modality for understanding the complex workings of the human brain, providing invaluable insights into cognitive processes, neurological disorders, and brain-computer interfaces. Nev…
  pubmed Arif M, Ur Rehman F, Sekanina L, Malik AS 2024 Oct 11 置信度 0.82
• Decoding motor imagery loaded on steady-state somatosensory evoked potential based on complex task-related component analysis.
  Motor Imagery (MI) recognition is one of the most critical decoding problems in brain- computer interface field. Combined with the steady-state somatosensory evoked potential (MI-SSSEP), this new paradigm can achieve higher recognition accuracy than the tradit…
  pubmed Wang X, Qi H 2024 Dec 置信度 0.82
• EEG-based sensorimotor neurofeedback for motor neurorehabilitation in children and adults: A scoping review.
  Therapeutic interventions for children and young people with dystonia and dystonic/dyskinetic cerebral palsy are limited. EEG-based neurofeedback is emerging as a neurorehabilitation tool. This scoping review maps research investigating EEG-based sensorimotor …
  pubmed Cioffi E, Hutber A, Molloy R, Murden S 等 2024 Nov 置信度 0.82
• Enhancing photoacoustic imaging for lung diagnostics and BCI communication: simulation of cavity structures artifact generation and evaluation of noise reduction techniques.
  Pandemics like COVID-19 have highlighted the potential of Photoacoustic imaging (PAI) for Brain-Computer Interface (BCI) communication and lung diagnostics. However, PAI struggles with the clear imaging of blood vessels in areas like the lungs and brain due to…
  pubmed Chai C, Yang X, Gao X, Shi J 等 2024 置信度 0.82
• Neuroinformatics Applications of Data Science and Artificial Intelligence.
  Leveraging vast neuroimaging and electrophysiological datasets, AI algorithms are uncovering patterns that offer unprecedented insights into brain structure and function. Neuroinformatics, the fusion of neuroscience and AI, is advancing technologies like brain…
  pubmed Dinov ID 2024 Oct 置信度 0.82
• Quantifying physical degradation alongside recording and stimulation performance of 980 intracortical microelectrodes chronically implanted in three humans for 956-2246 days.
  The clinical success of brain-machine interfaces depends on overcoming both biological and material challenges to ensure a long-term stable connection for neural recording and stimulation. Therefore, there is a need to quantify any damage that microelectrodes …
  pubmed Bjånes DA, Kellis S, Nickl R, Baker B 等 2024 Sep 10 置信度 0.82
• Blood diagnostic and prognostic biomarkers in amyotrophic lateral sclerosis.
  Amyotrophic lateral sclerosis is a devastating neurodegenerative disease for which the current treatment approaches remain severely limited. The principal pathological alterations of the disease include the selective degeneration of motor neurons in the brain,…
  pubmed Lv Y, Li H 2025 Sep 1 置信度 0.82
• Filter bank temporally delayed CCA for uncalibrated SSVEP-BCI.
  The uncalibrated brain-computer interface (BCI) system based on steady-state visual evoked potential (SSVEP) can omit the training process and is closer to the practical application. Filter bank canonical correlation analysis (FBCCA), as a classical approach o…
  pubmed Yin X, Yang C, Dong H, Liang J 等 2025 Feb 置信度 0.82
• Rethinking Our Approach to Accessibility in the Era of Rapidly Emerging Technologies.
  Accessibility has always played catch-up to the detriment of people with disabilities - and this appears to be exacerbated by the rapid advancements in technology. A key question becomes, can we better predict where technology will be in 10 or 20 years and dev…
  pubmed Vanderheiden G, Marte C, Bahram S 2024 置信度 0.82
• What stakeholders with neurodegenerative conditions value about speech and accuracy in development of BCI systems for communication.
  This research examined values of individuals with neurodegenerative conditions about features of speed and accuracy as they consider potential use of augmentative and alternative communication brain-computer interface systems (AAC-BCI). Sixty-six individuals w…
  pubmed Fried-Oken M, Kinsella M, Stevens I, Klein E 2024 置信度 0.82
• The Feasibility of AgileNudge+ Software to Facilitate Positive Behavioral Change: Mixed Methods Design.
  In today's digital age, web-based apps have become integral to daily life, driving transformative shifts in human behavior. "AgileNudge+" (Indiana University Center for Health Innovation and Implementation Science) is a web-based solution to simplify the proce…
  pubmed Shojaei F, Shojaei F, Desai AP, Long E 等 2024 Nov 13 置信度 0.82
• Case report: Novel use of clinical brain-computer interfaces in recreation programming for an autistic adolescent with co-occurring attention deficit hyperactivity disorder.
  In recent years, several autistic children and youth have shown interest in Holland Bloorview Kids Rehabilitation Hospital's clinical brain computer interface (BCI) program. Existing literature about BCI use among autistic individuals has focused solely on cog…
  pubmed Van Damme S, Mumford L, Johnson A, Chau T 2024 置信度 0.82
• Improving inter-session performance via relevant session-transfer for multi-session motor imagery classification.
  Motor imagery (MI)-based brain-computer interfaces (BCIs) using electroencephalography (EEG) have found practical applications in external device control. However, the non-stationary nature of EEG signals remains to obstruct BCI performance across multiple ses…
  pubmed Sung DJ, Kim KT, Jeong JH, Kim L 等 2024 Sep 15 置信度 0.82
• Atomic-engineered gradient tunable solid-state metamaterials.
  Metamaterial has been captivated a popular notion, offering photonic functionalities beyond the capabilities of natural materials. Its desirable functionality primarily relies on well-controlled conditions such as structural resonance, dispersion, geometry, fi…
  pubmed Yan Z, Handoko AD, Wu W, Yang C 等 2024 Sep 24 置信度 0.82
• Neuroprostheses move forward, in multiple languages.
  pubmed 2024 Oct 置信度 0.82
• Ethical challenges in translating brain-computer interfaces.
  pubmed Wexler A, Feinsinger A 2024 Oct 置信度 0.82
• Optimization of stimulus properties for SSVEP-based BMI system with a heads-up display to control in-vehicle features.
  Over the years, the driver-vehicle interface has been improved, but interacting with in-vehicle features can still increase distraction and affect road safety. This study aims to introduce brain-machine interface (BMI)- based solution to potentially enhance ro…
  pubmed Hamidi Shishavan H, Roy R, Golzari K, Singla A 等 2024 置信度 0.82
• Joint multi-feature extraction and transfer learning in motor imagery brain computer interface.
  Motor imagery brain computer interface (BCI) systems are considered one of the most crucial paradigms and have received extensive attention from researchers worldwide. However, the non-stationary from subject-to-subject transfer is a substantial challenge for …
  pubmed Cai M, Hong J, Miao Cai, Jie Hong 2024-09-17T13:15:04Z 置信度 0.82
• Machine learning and brain-computer interface approaches in prognosis and individualized care strategies for individuals with amyotrophic lateral sclerosis: A systematic review.
  Amyotrophic lateral sclerosis (ALS) characterized by progressive degeneration of motor neurons is a debilitating disease, posing substantial challenges in both prognosis and daily life assistance. However, with the advancement of machine learning (ML) which is…
  pubmed Kew SYN, Mok SY, Goh CH, Stephanie Yen Nee Kew 等 2024 Dec 置信度 0.82 Amyotrophic lateral sclerosisNeuroimagingMedicineDiseasePopulation
• Cortical ROI Importance Improves MI Decoding From EEG Using Fused Light Neural Network.
  Decoding motor imagery (MI) using deep learning in cortical level has potential in brain computer interface based intelligent rehabilitation. However, a mass of dipoles is inconvenient to extract the personalized features and requires a more complex neural net…
  pubmed Wang L, Li M, Xu D, Yang Y 2024 置信度 0.82
• Learning-based Free-Water Correction using Single-shell Diffusion MRI.
  Diffusion magnetic resonance imaging (dMRI) offers the ability to assess subvoxel brain microstructure through the extraction of biomarkers like fractional anisotropy, as well as to unveil brain connectivity by reconstructing white matter fiber trajectories. H…
  pubmed Yao T, Archer DB, Kanakaraj P, Newlin N 等 2024 Feb 置信度 0.82
• Low-Cost Dynamometer for Measuring and Regulating Wrist Extension and Flexion Motor Tasks in Electroencephalography Experiments.
  A brain-computer interface could control a bionic hand by interpreting electroencephalographic (EEG) signals associated with wrist extension (WE) and wrist flexion (WF) movements. Misinterpretations of the EEG may stem from variations in the force, speed and r…
  pubmed Mohamed AK, Aswat M, Aharonson V 2024 Sep 6 置信度 0.82
• Enhancing Brain-Computer Interfaces through Kriging-Based Fusion of Sparse Regression Partial Differential Equations to Counter Injection Molding View of Node Displacement Effects.
  Injection molding is an efficient and precise manufacturing technology that is widely used in the production of plastic products. In recent years, injection molding technology has made significant progress, especially with the combination of in-mold electronic…
  pubmed Chang H, Sun Y, Lu S, Lan Y 2024 Sep 3 置信度 0.82
• Robotics in Physical Rehabilitation: Systematic Review.
  As the global prevalence of motor disabilities continues to rise, there is a pressing need for advanced solutions in physical rehabilitation. This systematic review examines the progress and challenges of implementing robotic technologies in the motor rehabili…
  pubmed Banyai AD, Brișan C 2024 Aug 29 置信度 0.82
• Research on shared control of robots based on hybrid brain-computer interface.
  With the arrival of the new generation of artificial intelligence wave, new human-robot interaction technologies continue to emerge. Brain-computer interface (BCI) offers a pathway for state monitoring and interaction control between human and robot. However, …
  pubmed Zhang Z, Li M, Wei R, Liao W 等 2024 Dec 置信度 0.82
• A zero precision loss framework for EEG channel selection: enhancing efficiency and maintaining interpretability.
  The brain-computer interface (BCI) systems based on motor imagery typically rely on a large number of electrode channels to acquire information. The rational selection of electroencephalography (EEG) channel combinations is crucial for optimizing computational…
  pubmed Wang L, Wang J, Su H, Zhang X 等 2026 Feb 置信度 0.82
• Nanotechnology-driven Microemulsion Based Intranasal Delivery to Neurotechnology-driven Neuralink: Strategies to Improve Management of Neurodegenerative Disorders.
  Neurodegenerative disorder refers to malfunctioning of neurons their degradation leading to death of neurons. Among various neurodegenerative disorders APHD (Alzheimer's, Parkinson's, and Huntington's Disease) are particularly concerning due to their…
  pubmed Pragya, Bisht S, Parashar P 2024 Sep 12 置信度 0.82
• Prospectively identifying risks and controls for advanced brain-computer interfaces: A Networked Hazard Analysis and Risk Management System (Net-HARMS) approach.
  The introduction of advanced digital technologies continues to increase system complexity and introduce risks, which must be proactively identified and managed to support system resilience. Brain-computer interfaces (BCIs) are one such technology; however, the…
  pubmed King BJ, Read GJM, Salmon PM 2025 Jan 置信度 0.82
• Development and Evaluation of a Real-Time Phase-Triggered Stimulation Algorithm for the CorTec Brain Interchange.
  With the development and characterization of biomarkers that may reflect neural network state as well as a patient's clinical deficits, there is growing interest in more complex stimulation designs. While current implantable neuromodulation systems offer pathw…
  pubmed Cho H, Benjaber M, Alexis Gkogkidis C, Buchheit M 等 2024 置信度 0.82
• Constructing A Theoretical Model to Bridge Neural Transition with a State Switch in Bipolar Disorder.
  pubmed Guo X, Chen L, Lai J, Hu S 2025 Jan 置信度 0.82
• Editorial: Multimodal perceiving technologies in neuroscience and vision applications.
  pubmed Roman-Gonzalez A 2024 置信度 0.82
• Mapping cognitive activity from electrocorticography field potentials in humans performing NBack task.
  Objective . Advancements in data science and assistive technologies have made invasive brain-computer interfaces (iBCIs) increasingly viable for enhancing the quality of life in physically disabled individuals. Intracortical microelectrode implants are a commo…
  pubmed Johnston R, Boulay C, Miller K, Sachs A 2024 Sep 25 置信度 0.82
• Bridging minds and machines in Industry 5.0: neurobiological approach.
  In transitioning from Industry 4.0 to the forthcoming Industry 5.0, this research explores the fusion of the humanistic view and technological developments to redefine Continuing Engineering Education (CEE). Industry 5.0 introduces concepts like biomanufacturi…
  pubmed Rueda-Castro V, Azofeifa JD, Chacon J, Caratozzolo P 2024 置信度 0.82
• Federated Motor Imagery Classification for Privacy-Preserving Brain-Computer Interfaces.
  Training an accurate classifier for EEG-based brain-computer interface (BCI) requires EEG data from a large number of users, whereas protecting their data privacy is a critical consideration. Federated learning (FL) is a promising solution to this challenge. T…
  pubmed Jia T, Meng L, Li S, Liu J 等 2024 置信度 0.82
• Subject-Independent Wearable P300 Brain-Computer Interface Based on Convolutional Neural Network and Metric Learning.
  The calibration procedure for a wearable P300 brain-computer interface (BCI) greatly impact the user experience of the system. Each user needs to spend additional time establishing a decoder adapted to their own brainwaves. Therefore, achieving subject indepen…
  pubmed Hu L, Gao W, Lu Z, Shan C 等 2024 置信度 0.82
• Effective Phoneme Decoding With Hyperbolic Neural Networks for High-Performance Speech BCIs.
  Speech brain-computer interfaces (speech BCIs), which convert brain signals into spoken words or sentences, have demonstrated great potential for high-performance BCI communication. Phonemes are the basic pronunciation units. For monosyllabic languages such as…
  pubmed Tan X, Lian Q, Zhu J, Zhang J 等 2024 置信度 0.82
• Perception and control of a virtual body in immersive virtual reality for rehabilitation.
  This review explores recent advances in using immersive virtual reality to improve bodily perception and motor control in rehabilitation across musculoskeletal and neurological conditions, examining how virtual reality's unique capabilities can address the cha…
  pubmed Donegan T, Sanchez-Vives MV 2024 Dec 1 置信度 0.82
• Recent progress on smart lower prosthetic limbs: a comprehensive review on using EEG and fNIRS devices in rehabilitation.
  The global rise in lower limb amputation cases necessitates advancements in prosthetic limb technology to enhance the quality of life for affected patients. This review paper explores recent advancements in the integration of EEG and fNIRS modalities for smart…
  pubmed AlQahtani NJ, Al-Naib I, Althobaiti M 2024 置信度 0.82
• Improved motor imagery training for subject's self-modulation in EEG-based brain-computer interface.
  For the electroencephalogram- (EEG-) based motor imagery (MI) brain-computer interface (BCI) system, more attention has been paid to the advanced machine learning algorithms rather than the effective MI training protocols over past two decades. However, it is …
  pubmed Xu Y, Jie L, Jian W, Yi W 等 2024 置信度 0.82
• I see artifacts: ICA-based EEG artifact removal does not improve deep network decoding across three BCI tasks.
  Objective. In this paper, we conduct a detailed investigation on the effect of independent component (IC)-based noise rejection methods in neural network classifier-based decoding of electroencephalography (EEG) data in different task datasets. Approach. We ap…
  pubmed Kang T, Chen Y, Wallraven C 2024 Dec 20 置信度 0.82
• Integrating spatial and temporal features for enhanced artifact removal in multi-channel EEG recordings.
  Objective. Various artifacts in electroencephalography (EEG) are a big hurdle to prevent brain-computer interfaces from real-life usage. Recently, deep learning-based EEG denoising methods have shown excellent performance. However, existing deep network design…
  pubmed Yin J, Liu A, Wang L, Qian R 等 2024 Sep 19 置信度 0.82
• "As if it were my own hand": inducing the rubber hand illusion through virtual reality for motor imagery enhancement.
  Brain-computer interfaces (BCI) are widely used in the field of disability assistance and rehabilitation, and virtual reality (VR) is increasingly used for visual guidance of BCI-MI (motor imagery). Therefore, how to improve the quality of electroencephalogram…
  pubmed Cheng S, Liu Y, Gao Y, Dong Z 2024 Nov 置信度 0.82
• Automatic Feature Selection for Sensorimotor Rhythms Brain-Computer Interface Fusing Expert and Data-Driven Knowledge.
  Early brain-computer interface (BCI) systems were mainly based on prior neurophysiological knowledge coupled with feedback training, while state-of-the-art interfaces rely on data-driven, machine learning (ML)-oriented methods. Despite the advances in BCI that…
  pubmed Sultana M, Perdikis S 2024 置信度 0.82
• Brain-Controlled Augmented Hearing for Spatially Moving Conversations in Multi-Talker Environments.
  Focusing on a specific conversation amidst multiple interfering talkers is challenging, especially for those with hearing loss. Brain-controlled assistive hearing devices aim to alleviate this problem by enhancing the attended speech based on the listener's ne…
  pubmed Choudhari V, Han C, Bickel S, Mehta AD 等 2024 Nov 置信度 0.82
• Design and application of pneumatic rehabilitation glove system based on brain-computer interface.
  Stroke has been the second leading cause of death and disability worldwide. With the innovation of therapeutic schedules, its death rate has decreased significantly but still guides chronic movement disorders. Due to the lack of independent activities and mini…
  pubmed Chen C, Song Y, Chen D, Zhu J 等 2024 Sep 1 置信度 0.82
• Simultaneous EEG-fNIRS Data Classification Through Selective Channel Representation and Spectrogram Imaging.
  The integration of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) can facilitate the advancement of brain-computer interfaces (BCIs). However, existing research in this domain has grappled with the challenge of the efficient sel…
  pubmed Bunterngchit C, Wang J, Hou ZG 2024 置信度 0.82
• Letter to editor: "Neuralink's brain implant: a vision for enhanced human-machine integration".
  pubmed Imath M, Ragavendran C 2024 Sep 7 置信度 0.82
• Estimating cognitive workload using a commercial in-ear EEG headset.
  Objective. This study investigated the potential of estimating various mental workload levels during two different tasks using a commercial in-ear electroencephalography (EEG) system, the IDUN 'Guardian'. Approach. Participants performed versions of two classi…
  pubmed Tremmel C, Krusienski DJ, Schraefel M 2024 Dec 2 置信度 0.82
• Community-based reconstruction and simulation of a full-scale model of the rat hippocampus CA1 region.
  The CA1 region of the hippocampus is one of the most studied regions of the rodent brain, thought to play an important role in cognitive functions such as memory and spatial navigation. Despite a wealth of experimental data on its structure and function, it ha…
  pubmed Romani A, Antonietti A, Bella D, Budd J 等 2024 Nov 置信度 0.82
• Design of EEG based thought identification system using EMD & deep neural network.
  Biological communication system for neurological disorder patients is similar to the Brain Computer Interface in a way that it facilitates the connection to the outside world in real time. The interdisciplinary field of Electroencephalogram based message depic…
  pubmed Agrawal R, Dhule C, Shukla G, Singh S 等 2024 Nov 4 置信度 0.82
• Temporal attention fusion network with custom loss function for EEG-fNIRS classification.
  Objective. Methods that can detect brain activities accurately are crucial owing to the increasing prevalence of neurological disorders. In this context, a combination of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) offers a p…
  pubmed Bunterngchit C, Wang J, Su J, Wang Y 等 2024 Nov 20 置信度 0.82
• Adenosine-Dependent Arousal Induced by Astrocytes in a Brainstem Circuit.
  Astrocytes play a crucial role in regulating sleep-wake behavior. However, how astrocytes govern a specific sleep-arousal circuit remains unknown. Here, the authors show that parafacial zone (PZ) astrocytes responded to sleep-wake cycles with state-differentia…
  pubmed Zhu Y, Ma J, Li Y, Gu M 等 2024 Dec 置信度 0.82
• Motor task-to-task transfer learning for motor imagery brain-computer interfaces.
  Motor imagery (MI) is one of the popular control paradigms in the non-invasive brain-computer interface (BCI) field. MI-BCI generally requires users to conduct the imagination of movement (e.g., left or right hand) to collect training data for generating a cla…
  pubmed Gwon D, Ahn M 2024 Nov 15 置信度 0.82
• Nanostructured Photonics Probes: A Transformative Approach in Neurotherapeutics and Brain Circuitry.
  Neuroprobes that use nanostructured photonic interfaces are capable of multimodal sensing, stimulation, and imaging with unprecedented spatio-temporal resolution. In addition to electrical recording, optogenetic modulation, high-resolution optical imaging, and…
  pubmed Ahmed Taha B, Addie AJ, Saeed AQ, Haider AJ 等 2024 Dec 6 置信度 0.82
• Intravascular delivery of an ultraflexible neural electrode array for recordings of cortical spiking activity.
  Although intracranial neural electrodes have significantly contributed to both fundamental research and clinical treatment of neurological diseases, their implantation requires invasive surgery to open craniotomies, which can introduce brain damage and disrupt…
  pubmed Wang X, Wu S, Yang H, Bao Y 等 2024 Nov 1 置信度 0.82
• Influence of Temporal and Frequency Selective Patterns Combined with CSP Layers on Performance in Exoskeleton-Assisted Motor Imagery Tasks.
  Common Spatial Pattern (CSP) has been recognized as a standard and powerful method for the identification of Electroencephalography (EEG)-based Motor Imagery (MI) tasks when implementing brain-computer interface (BCI) systems towards the motor rehabilitation o…
  pubmed Guerrero-Mendez CD, Blanco-Diaz CF, Rivera-Flor H, Fabriz-Ulhoa PH 等 2024 Jun 置信度 0.82
• Single-Molecule Bioelectronic Sensors with AI-Aided Data Analysis: Convergence and Challenges.
  Single-molecule bioelectronic sensing, a groundbreaking domain in biological research, has revolutionized our understanding of molecules by revealing deep insights into fundamental biological processes. The advent of emergent technologies, such as nanogapped e…
  pubmed Yang Y, Li Y, Tang L, Li J 2024 Oct 28 置信度 0.82
• HYBRIDMINDS-summary and outlook of the 2023 international conference on the ethics and regulation of intelligent neuroprostheses.
  Neurotechnology and Artificial Intelligence (AI) have developed rapidly in recent years with an increasing number of applications and AI-enabled devices that are about to enter the market. While promising to substantially improve quality of life across various…
  pubmed Buthut M, Starke G, Akmazoglu TB, Colucci A 等 2024 置信度 0.82
• A leadless power transfer and wireless telemetry solutions for an endovascular electrocorticography.
  Objective . Endovascular brain-computer interfaces (eBCIs) offer a minimally invasive way to connect the brain to external devices, merging neuroscience, engineering, and medical technology. Currently, solutions for endovascular electrocorticography (ECoG) inc…
  pubmed Xu Z, Khazaee M, Duy Truong N, Havenga D 等 2024 Nov 12 置信度 0.82
• Creating ionic current pathways: A non-implantation approach to achieving cortical electrical signals for brain-computer interface.
  This study introduces a novel method for acquiring brain electrical signals comparable to intracranial recordings without the health risks associated with implanted electrodes. We developed a technique using ultrasonic tools to create micro-holes in the skull …
  pubmed Sun Y, Gao Y, Shen A, Sun J 等 2025 Jan 15 置信度 0.82
• Cell-specific spatial profiling of targeted protein expression to characterize the impact of intracortical microelectrode implantation on neuronal health.
  Intracortical microelectrode arrays (MEAs) can record neuronal activity and advance brain-computer interface (BCI) devices. Implantation of the invasive MEA kills local neurons, which has been documented using immunohistochemistry (IHC). Neuronal nuclear prote…
  pubmed Druschel LN, Kasthuri NM, Song SS, Wang JJ 等 2024 Dec 4 置信度 0.82
• Posterior Basolateral Amygdala is a Critical Amygdaloid Area for Temporal Lobe Epilepsy.
  The amygdaloid complex consists of multiple nuclei and is a key node in controlling temporal lobe epilepsy (TLE) in both human and animal model studies. However, the specific nucleus in the amygdaloid complex and the neural circuitry governing seizures remain …
  pubmed Sun YH, Hu BW, Tan LH, Lin L 等 2024 Dec 置信度 0.82
• Effects of oxycodone on placental lineages: Evidence from the transcriptome profile of mouse trophoblast giant cells.
  Pregnant women are often prescribed or abuse opioid drugs. The placenta is likely the key to understanding how opioids cause adverse pregnancy outcomes. Maternal oxycodone (OXY) exposure of pregnant mice leads to disturbances in the layer of invasive parietal …
  pubmed Lyu Z, Kinkade JA, Bivens NJ, Roberts RM 等 2024 Nov 5 置信度 0.82
• Development and preliminary evaluation of a grid design application for adults and children using scanning and bci-based augmentative and alternative communication.
  Augmentative and alternative communication (AAC) supports offer communication aids for individuals with severe speech and physical impairments. This study presents the development and proof of concept for an iPad application designed to evaluate the design pre…
  pubmed Pitt KM 2024 Oct 30 置信度 0.82
• A flexible, stable, semi-dry electrode with low impedance for electroencephalography recording.
  Brain-computer interfaces (BCIs) provide promising prospects for the field of healthcare and rehabilitation, presenting significant advantages for humanity. The development of electrodes that exhibit satisfactory performance characteristics, including high ele…
  pubmed Zhu Y, Bayin C, Li H, Shu X 等 2024 Oct 23 置信度 0.82
• HASTF: a hybrid attention spatio-temporal feature fusion network for EEG emotion recognition.
  EEG-based emotion recognition has gradually become a new research direction, known as affective Brain-Computer Interface (aBCI), which has huge application potential in human-computer interaction and neuroscience. However, how to extract spatio-temporal fusion…
  pubmed Hu F, Wang F, Bi J, An Z 等 2024 置信度 0.82
• Compact convolutional transformer for subject-independent motor imagery EEG-based BCIs.
  Motor imagery electroencephalography (EEG) analysis is crucial for the development of effective brain-computer interfaces (BCIs), yet it presents considerable challenges due to the complexity of the data and inter-subject variability. This paper introduces EEG…
  pubmed Keutayeva A, Fakhrutdinov N, Abibullaev B 2024 Oct 28 置信度 0.82
• Ethical considerations for the use of brain-computer interfaces for cognitive enhancement.
  Brain-computer interfaces (BCIs) enable direct communication between the brain and external computers, allowing processing of brain activity and the ability to control external devices. While often used for medical purposes, BCIs may also hold great promise fo…
  pubmed Gordon EC, Seth AK 2024 Oct 置信度 0.82
• Evaluation of consumer-grade wireless EEG systems for brain-computer interface applications.
  With the growing popularity of consumer-grade electroencephalogram (EEG) devices for health, entertainment, and cognitive research, assessing their signal quality is essential. In this study, we evaluated four consumer-grade wireless and dry-electrode EEG syst…
  pubmed Lee S, Kim M, Ahn M 2024 Nov 置信度 0.82
• A 4-DOF Exosuit Using a Hybrid EEG-Based Control Approach for Upper-Limb Rehabilitation.
  Rehabilitation devices, such as traditional rigid exoskeletons or exosuits, have been widely used to rehabilitate upper limb function post-stroke. In this paper, we have developed an exosuit with four degrees of freedom to enable users to involve more joints i…
  pubmed Tang Z, Cui Z, Wang H, Liu P 等 2024 置信度 0.82
• [Discussion on Magnetic Resonance Compatibility of Implantable Brain-Computer Interface Devices].
  Brain-computer interface (BCI) devices are crucial tools for neural stimulation and recording, offering broad prospects in the diagnosis and treatment of neurological disorders. Furthermore, magnetic resonance imaging (MRI) is an effective and non-invasive tec…
  pubmed Jin K, Liu X, Hu S, Li Y 等 2024 Sep 30 置信度 0.82
• Cross-Task Differences in Frontocentral Cortical Activations for Dynamic Balance in Neurotypical Adults.
  Although significant progress has been made in understanding the cortical correlates underlying balance control, these studies focused on a single task, limiting the ability to generalize the findings. Different balance tasks may elicit cortical activations in…
  pubmed Magruder RD, Kukkar KK, Contreras-Vidal JL, Parikh PJ 2024 Oct 15 置信度 0.82
• SoftBoMI: a non-invasive wearable body-machine interface for mapping movement of shoulder to commands.
  Objective. Customized human-machine interfaces for controlling assistive devices are vital in improving the self-help ability of upper limb amputees and tetraplegic patients. Given that most of them possess residual shoulder mobility, using it to generate comm…
  pubmed Liu R, Song Q, Ma T, Pan H 等 2024 Nov 8 置信度 0.82
• Enhancing ERD Activation and Functional Connectivity via the Sixth-Finger Motor Imagery in Stroke Patients.
  Motor imagery (MI) is widely employed in stroke rehabilitation due to the event-related desynchronization (ERD) phenomenon in sensorimotor cortex induced by MI is similar to actual movement. However, the traditional BCI paradigm, in which the patient imagines …
  pubmed Wang Z, Liu Y, Huang S, Huang H 等 2024 置信度 0.82
• Real-Time Home Automation System Using BCI Technology.
  A Brain-Computer Interface (BCI) processes and converts brain signals to provide commands to output devices to carry out certain tasks. The main purpose of BCIs is to replace or restore the missing or damaged functions of disabled people, including in neuromus…
  pubmed Drăgoi MV, Nisipeanu I, Frimu A, Tălîngă AM 等 2024 Oct 1 置信度 0.82
• Adaptive vs. Conventional Deep Brain Stimulation: One-Year Subthalamic Recordings and Clinical Monitoring in a Patient with Parkinson's Disease.
  Conventional DBS (cDBS) for Parkinson's disease uses constant, predefined stimulation parameters, while the currently available adaptive DBS (aDBS) provides the possibility of adjusting current amplitude with respect to subthalamic activity in the beta band (1…
  pubmed Caffi L, Romito LM, Palmisano C, Aloia V 等 2024 Sep 30 置信度 0.82
• Integrating Electroencephalography Source Localization and Residual Convolutional Neural Network for Advanced Stroke Rehabilitation.
  Motor impairments caused by stroke significantly affect daily activities and reduce quality of life, highlighting the need for effective rehabilitation strategies. This study presents a novel approach to classifying motor tasks using EEG data from acute stroke…
  pubmed Kaviri SM, Vinjamuri R 2024 Sep 27 置信度 0.82
• Multimodal human computer interaction of wheelchairs supporting lower limb active rehabilitation.
  Currently, an important challenge in stroke rehabilitation is how to effectively restore motor functions of lower limbs. This paper presents multimodal human computer interaction (HCI) of wheelchairs supporting lower limb active rehabilitation. First, multimod…
  pubmed Hong J, Cai M, Qin X 2026 Mar 置信度 0.82
• Relationship of SSVEP response between flash frequency conditions.
  This study delves into the application of Brain-Computer Interfaces (BCIs), focusing on exploiting Steady-State Visual Evoked Potentials (SSVEPs) as communication tools for individuals facing mobility impairments. SSVEP-BCI systems can swiftly transmit substan…
  pubmed Chang CT, Pai KJ, Huang CH, Chou CY 等 2024 置信度 0.82
• Optimizing user experience in SSVEP-BCI systems.
  The emergence of brain-computer interface (BCI) technology provides enormous potential for human medical and daily applications. Therefore, allowing users to tolerate the visual response of SSVEP for a long time has always been an important issue in the SSVEP-…
  pubmed Chang CT, Pai KJ, Huang CH, Chou CY 等 2024 置信度 0.82
• A Survey of Surrogates and Health Care Professionals Indicates Support of Cognitive Motor Dissociation-Assisted Prognostication.
  Prognostication of patients with acute disorders of consciousness is imprecise but more accurate technology-supported predictions, such as cognitive motor dissociation (CMD), are emerging. CMD refers to the detection of willful brain activation following motor…
  pubmed Heinonen GA, Carmona JC, Grobois L, Kruger LS 等 2025 Jun 置信度 0.82
• Neural interfaces: Bridging the brain to the world beyond healthcare.
  Neural interfaces, emerging at the intersection of neurotechnology and urban planning, promise to transform how we interact with our surroundings and communicate. By recording and decoding neural signals, these interfaces facilitate direct connections between …
  pubmed Xu S, Liu Y, Lee H, Li W 2024 Oct 置信度 0.82
• Sensory-substitution based sound perception using a spinal computer-brain interface.
  Sensory substitution offers a promising approach to restore lost sensory functions. Here we show that spinal cord stimulation (SCS), typically used for chronic pain management, can potentially serve as a novel auditory sensory substitution device. We recruited…
  pubmed Miklós G, Halász L, Hasslberger M, Toth E 等 2024 Oct 22 置信度 0.82
• Classification of EEG evoked in 2D and 3D virtual reality: traditional machine learning versus deep learning.
  Backgrounds . Virtual reality (VR) simulates real-life events and scenarios and is widely utilized in education, entertainment, and medicine. VR can be presented in two dimensions (2D) or three dimensions (3D), with 3D VR offering a more realistic and immersiv…
  pubmed Zuo M, Yu B, Sui L 2024 Nov 5 置信度 0.82
• Enhancing learning experiences: EEG-based passive BCI system adapts learning speed to cognitive load in real-time, with motivation as catalyst.
  Computer-based learning has gained popularity in recent years, providing learners greater flexibility and freedom. However, these learning environments do not consider the learner's mental state in real-time, resulting in less optimized learning experiences. T…
  pubmed Beauchemin N, Charland P, Karran A, Boasen J 等 2024 置信度 0.82
• A Hardware-Efficient Novelty-Aware Spike Sorting Approach for Brain-Implantable Microsystems.
  Unsupervised spike sorting, a vital processing step in real-time brain-implantable microsystems, is faced with the prominent challenge of managing nonstationarity in neural signals. In long-term recordings, spike waveforms gradually change and new source neuro…
  pubmed Ahmadi-Dastgerdi N, Hosseini-Nejad H, Alinejad-Rokny H 2024 Dec 置信度 0.82
• Task-oriented EEG denoising generative adversarial network for enhancing SSVEP-BCI performance.
  Objective. The quality of electroencephalogram (EEG) signals directly impacts the performance of brain-computer interface (BCI) tasks. Many methods have been proposed to eliminate noise from EEG signals, but most of these methods focus solely on signal denoisi…
  pubmed Zeng P, Fan L, Luo Y, Shen H 等 2024 Nov 5 置信度 0.82
• Adversarial artifact detection in EEG-based brain-computer interfaces.
  Objective . machine learning has achieved significant success in electroencephalogram (EEG) based brain-computer interfaces (BCIs), with most existing research focusing on improving the decoding accuracy. However, recent studies have shown that EEG-based BCIs …
  pubmed Chen X, Meng L, Xu Y, Wu D 2024 Oct 30 置信度 0.82
• Silk fibroin-based bioelectronic devices for high-sensitivity, stable, and prolonged in vivo recording.
  Silk fibroin, recognized for its biocompatibility and modifiable properties, has significant potential in bioelectronics. Traditional silk bioelectronic devices, however, face rapid functional losses in aqueous or in vivo environments due to high water absorpt…
  pubmed Yang H, Zhu Z, Ni S, Wang X 等 2025 Jan 1 置信度 0.82
• Multi-source domain transfer network based on subdomain adaptation and minimum class confusion for EEG emotion recognition.
  Electroencephalogram (EEG) signals, which objectively reflect the state of the brain, are widely favored in emotion recognition research. However, the presence of cross-session and cross-subject variation in EEG signals has hindered the practical implementatio…
  pubmed Zhu L, Xu M, Huang A, Zhang J 等 2026 Mar 置信度 0.82
• Neurorights in the Constitution: from neurotechnology to ethics and politics.
  Neuroimaging technologies such as brain-computer interfaces and neurofeedback have evolved rapidly as new tools for cognitive neuroscience and as potential clinical interventions. However, along with these developments, concern has grown based on the fear of t…
  pubmed Ruiz S, Valera L, Ramos P, Sitaram R 等 2024 Dec 2 置信度 0.82 ConstitutionNeuroethicsNeurocognitiveNeurofeedbackPolitics
• Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation.
  Neurofeedback (NF) is endogenous neuromodulation of circumscribed brain circuitry. While its use of real-time brain activity in a closed-loop system is similar to brain-computer interfaces, instead of controlling an external device like the latter, the goal of…
  pubmed Sulzer J, Papageorgiou TD, Goebel R, Hendler T 2024 Dec 2 置信度 0.82
• Mechanisms of brain self-regulation: psychological factors, mechanistic models and neural substrates.
  While neurofeedback represents a promising tool for neuroscience and a brain self-regulation approach to psychological rehabilitation, the field faces several problems and challenges. Current research has shown great variability and even failure among human pa…
  pubmed Sitaram R, Sanchez-Corzo A, Vargas G, Cortese A 等 2024 Dec 2 置信度 0.82
• Towards imagined speech: Identification of brain states from EEG signals for BCI-based communication systems.
  The electroencephalogram (EEG) based brain-computer interface (BCI) system employing imagined speech serves as a mechanism for decoding EEG signals to facilitate control over external devices or communication with the external world at the moment the user desi…
  pubmed V HM, Begum BS 2025 Feb 4 置信度 0.82
• Attention Induced Dual Convolutional-Capsule Network (AIDC-CN): A deep learning framework for motor imagery classification.
  In recent times, Electroencephalography (EEG)-based motor imagery (MI) decoding has garnered significant attention due to its extensive applicability in healthcare, including areas such as assistive robotics and rehabilitation engineering. Nevertheless, the de…
  pubmed Chowdhury RS, Bose S, Ghosh S, Konar A 2024 Dec 置信度 0.82
• A brief survey on human activity recognition using motor imagery of EEG signals.
  Human being's biological processes and psychological activities are jointly connected to the brain. So, the examination of human activity is more significant for the well-being of humans. There are various models for brain activity detection considering neuroi…
  pubmed Mahalungkar SP, Shrivastava R, Angadi S 2024 Oct 置信度 0.82
• Reducing power requirements for high-accuracy decoding in iBCIs.
  Objective. Current intracortical brain-computer interfaces (iBCIs) rely predominantly on threshold crossings ('spikes') for decoding neural activity into a control signal for an external device. Spiking data can yield high accuracy online control during comple…
  pubmed Karpowicz BM, Bhaduri B, Nason-Tomaszewski SR, Jacques BG 等 2024 Nov 1 置信度 0.82
• Identification of perceived sentences using deep neural networks in EEG.
  Objetive . Decoding speech from brain activity can enable communication for individuals with speech disorders. Deep neural networks (DNNs) have shown great potential for speech decoding applications. However, the limited availability of large datasets containi…
  pubmed Valle C, Mendez-Orellana C, Herff C, Rodriguez-Fernandez M 2024 Oct 30 置信度 0.82
• Population clustering of structural brain aging and its association with brain development.
  Structural brain aging has demonstrated strong inter-individual heterogeneity and mirroring patterns with brain development. However, due to the lack of large-scale longitudinal neuroimaging studies, most of the existing research focused on the cross-sectional…
  pubmed Duan H, Shi R, Kang J, Banaschewski T 等 2024 Oct 18 置信度 0.82