Suchergebnisse - "Brain Computer Interface"

Tensor decomposition of EEG signals for transfer learning applications

Autoren: Karlsson, Linda Fallenius, Emma Bergeling, Carolina et al.

Quelle: eLLIIT – The Linköping – Lund Initiative on IT and Mobile Communication Brain-Computer Interfaces. 11(4):178-192

Schlagwörter: BCI calibration, Brain–computer interface, similarity measure, tensor decomposition, transfer learning, Contrastive Learning, Brain–computer interface calibration, Calibration problems, EEG signals, matrix, Motor imagery tasks, S-factor, Universal structures, Tensors

Dateibeschreibung: electronic

Zugangs-URL: https://urn.kb.se/resolve?urn=urn:nbn:se:bth-26998
https://doi.org/10.1080/2326263X.2024.2401663

Using EEG-based BCI settings and brain-state dependent stimulation as research tools for hypothesis-testing in cognitive neuroscience: a test-bench for brain-behavioural

Autoren: Vigué-Guix, Irene

Weitere Verfasser: University/Department: Universitat Pompeu Fabra. Departament de Tecnologies de la Informació i les Comunicacions

Thesis Advisors: Soto-Faraco, Salvador

Quelle: TDX (Tesis Doctorals en Xarxa)

Schlagwörter: Brain-computer interface, Brain oscillations, Brain-state dependent stimulation, Behaviour, Reaction time, Alpha rhythm, Visual perception, Spatial attention, Human cognition augmentation, Interfaz cerebro-ordenador, Oscilaciones cerebrales, Estimulación dependiente del estado cerebral, Comportamiento, Tiempo de reacción, Ritmo alfa, Percepción visual, Atención espacial, Aumento de la cognición humana, Interfície cervell-ordinador, Oscil·lacions cerebrals, Estimulació dependent de l'estat cerebral, Comportament, Temps de reacció, Ritme alfa, Percepció visual, Atenció espacial, Augment de la cognició humana

Dateibeschreibung: application/pdf

Zugangs-URL: http://hdl.handle.net/10803/675090

Designing Multifunctional Microneedles in Biomedical Engineering: Materials, Methods, and Applications

Autoren: Ling Liu Fangyan Wang Xiang Chen et al.

Quelle: Int J Nanomedicine
International Journal of Nanomedicine, Vol Volume 20, Iss Issue 1, Pp 8693-8728 (2025)

Schlagwörter: Medicine (General), R5-920, brain-computer interface, minimally invasive technique, Review, Biomedical engineering, multifunctional microneedle

Zugangs-URL: https://doaj.org/article/4eb587778fe74230b22e0f8469ee7bfb

FT-DropBlock: A Novel Approach for Spatiotemporal Regularization in EEG-based Convolutional Neural Networks

Autoren: Nzakuna Pierre Paciello V. Gallo V. et al.

Quelle: 2025 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). :1-6

Schlagwörter: Brain-Computer Interface, Electroencephalography, CNN, DropBlock, Regularization

SIG PhysioCHI: Human-Centered Physiological Computing in Practice: Human-Centered Physiological Computing in Practice

Autoren: Teodora Mitrevska Benjamin Tag Monica Perusquia-Hernandez et al.

Quelle: Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems. :1-5

Schlagwörter: Brain-Computer Interface, EMG, Open Science, ECG, Eye Tracking, fNIRS, EEG, Electrodermal Activity, Physiological Computing

Speech motor cortex enables BCI cursor control and click

Autoren: Singer-Clark, Tyler Hou, Xianda Card, Nicholas S et al.

Quelle: Journal of Neural Engineering. 22(3)

Schlagwörter: Engineering, Biomedical Engineering, ALS, Bioengineering, Assistive Technology, Brain Disorders, Neurodegenerative, Rehabilitation, Neurosciences, Rare Diseases, Clinical Trials and Supportive Activities, Clinical Research, Neurological, Humans, Male, Middle Aged, Amyotrophic Lateral Sclerosis, Brain-Computer Interfaces, Electrodes, Implanted, Electroencephalography, Motor Cortex, Speech, brain-computer interface, ventral precentral gyrus, cursor control, speech motor cortex, Clinical Sciences, Biomedical engineering

Zugangs-URL: https://escholarship.org/uc/item/9hc9t8xf

DESIGN AND DEVELOPMENT OF A LINEAR MOTORIZED SOFT ROBOTICS EXO-MUSCULAR (SMER) GLOVE

Autoren: Nastaran Reza Nazar Zadeh Jennifer Dela Cruz Mohammad Tabibi

Quelle: Proceedings on Engineering Sciences, Vol 7, Iss 2, Pp 1315-1324 (2025)

Schlagwörter: soft robotics, linear motorized unit, exoskeleton, brain-computer interface, TA1-2040, shape-memory alloy, Engineering (General). Civil engineering (General), exo muscular

Zugangs-URL: https://doaj.org/article/c23c5d07931b478cba51729ef805657f

An Ultra-Low Power Wearable BMI System With Continual Learning Capabilities

Autoren: Lan Mei Thorir Mar Ingolfsson Cristian Cioflan et al.

Quelle: IEEE Transactions on Biomedical Circuits and Systems. 19:511-522

Schlagwörter: Signal Processing (eess.SP), Wearable EEG, Brain-computer interface, On-device learning, FOS: Electrical engineering, electronic engineering, information engineering, Deep learning, EEG, Continual learning, Systems and Control (eess.SY), Electrical Engineering and Systems Science - Signal Processing, Wearable healthcare, Electrical Engineering and Systems Science - Systems and Control

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/39255091
http://arxiv.org/abs/2409.10654

Stroke Rehabilitation Targeting the Cerebello-Cerebral Neural Circuit： Advances from Neuromodulation to Closed-Loop Brain-Computer Interface Technology

Autoren: GUO Shuanghui ZHANG Yumei

Quelle: 康复学报, Vol 35, Pp 260-264 (2025)

Schlagwörter: cerebellar-cortical circuit, neuromodulation, brain-computer interface, Medicine, stroke, rehabilitation

Zugangs-URL: https://doaj.org/article/083312856710407e955140a70f4cb1c2

Effects of Intermittent Theta Burst Stimulation Combined with Motor Imagery-Based Brain Computer Interface Training on Hand Function after Stroke

Autoren: LIAN Yawen LI Yinghua LI He et al.

Quelle: 康复学报, Vol 35, Pp 242-249 (2025)

Schlagwörter: motor imagery, Medicine, hand function, intermittent theta burst stimulation, brain computer interface, stroke

Zugangs-URL: https://doaj.org/article/c652c87a2bca44c6b67e9e5a409d090c

Motor imagery classification using a novel CNN in EEG-BCI with common average reference and sliding window techniques

Autoren: Konda Gurava Reddy Atla Rajeev Sharma

Quelle: Alexandria Engineering Journal, Vol 120, Iss, Pp 532-546 (2025)

Schlagwörter: Electroencephalogram, Motor imagery, Brain-computer interface, Convolutional neural networks, TA1-2040, Engineering (General). Civil engineering (General)

Zugangs-URL: https://doaj.org/article/a2ddf5b4c57f4c34b73e9289518a7dbe

The Effect of User Learning for Online EEG Decoding of Upper-Limb Movement Intention

Autoren: Matteo Ceradini Stefano Tortora Silvestro Micera et al.

Quelle: IEEE Transactions on Medical Robotics and Bionics. 7:633-641

Schlagwörter: brain-computer interface, EEG, movement intention, online decoding, user learning

Unsupervised Domain Adaptation With Synchronized Self-Training for Cross- Domain Motor Imagery Recognition

Autoren: Peiyin Chen Xiaofeng Liu Chao Ma et al.

Weitere Verfasser: Peiyin Chen Xiaofeng Liu Chao Ma et al.

Quelle: IEEE Journal of Biomedical and Health Informatics. 29:3664-3677

Schlagwörter: Adult, Male, electroencephalogram (EEG), brain-computer interface (BCI), Electroencephalography, Signal Processing, Computer-Assisted, synchronized self training (SST), Young Adult, unsupervised domain adaptation (UDA), QC Physics, Brain-Computer Interfaces, Imagination, Humans, Female, Motor imagery (MI), QC, Algorithms, Unsupervised Machine Learning

Dateibeschreibung: application/pdf

Zugangs-URL: https://pubmed.ncbi.nlm.nih.gov/40031262

Application of Motor Imagery in Stroke Rehabilitation

Autoren: WANG Jiayu WANG Jiening QI Rui

Quelle: 康复学报, Pp 1-8 (2025)
康复学报, Vol 35, Pp 205-211 (2025)

Schlagwörter: motor imagery, Functional impairment, Medicine, motor imagery brain-computer interface, stroke, rehabilitation therapy

Zugangs-URL: https://doaj.org/article/68ab417e8c5a47ed83eba3388076444e
https://doaj.org/article/3587716cab9542b99398ff7dd0191edc

Application Prescription of Brain-Computer Interface Based on Motor Imagery in Post-Stroke Dysfunction

Autoren: JIANG Shanshan QIU Zhiqing YOU Tingting et al.

Quelle: 康复学报, Vol 35, Pp 212-220 (2025)

Schlagwörter: neurorehabilitation, dysfunction, motor imagery, brain-computer interface, Medicine, application prescription, stroke

Zugangs-URL: https://doaj.org/article/3f493516ffe9425d9c7236dc28f98db1

Clinical Efficacy of Motor Imagery-Based Brain-Computer Interface Collaborative Training Combined with Conventional Rehabilitation Therapy on Subacute Stroke Patients with Hemiplegia

Autoren: ZHANG Wendong LIU Xiaolu YAN Yanning et al.

Quelle: 康复学报, Vol 35, Pp 146-151 (2025)

Schlagwörter: motor imagery, upper limb motor function, brain-computer interface, hemiplegia, Medicine, stroke, functional electrical stimulation, brain-computer collaborative training

Zugangs-URL: https://doaj.org/article/bc45f711710a4962966cd4b1e8426699

A glimpse ahead: Forecasting 5.5-s human vigilance for enhanced safety in Industry 5.0

Autoren: Ettore Cinquetti Ilaria Siviero Fabio Babiloni et al.

Quelle: Biocybernetics and Biomedical Engineering. 45:258-268

Schlagwörter: Brain-computer interface, Electroencephalography, Vigilance, Forecasting, Industry 5.0, Deep-learning

Is Gamification of Neurofeedback Training effective for ADHD treatment? A Systematic Review

Autoren: Kohnen, Henriette Mavromoustakos-Blom, Paris Alimardani, Maryam

Quelle: 2025 13th International Conference on Brain-Computer Interface (BCI). :1-9

Schlagwörter: ADHD, brain-computer interface (BCI), neurofeedback (NF) training, games

Zugangs-URL: https://research.vu.nl/en/publications/70550d51-5b7d-4c7c-bf2e-1bf0caae232b
https://doi.org/10.1109/BCI65088.2025.10931381
https://hdl.handle.net/1871.1/70550d51-5b7d-4c7c-bf2e-1bf0caae232b

From Post-Median Nerve Stimulation ERD to MI-BCI Expertise Prediction

Autoren: Cueva, Valérie Marissens Lotte, Fabien Bougrain, Laurent et al.

Weitere Verfasser: Cueva, Valérie Marissens Lotte, Fabien Bougrain, Laurent et al.

Quelle: 2025 13th International Conference on Brain-Computer Interface (BCI). :1-6

Schlagwörter: Performances, Electrophysiology, Brain-Computer Interface, Predictors, Median Nerve Stimulation, Motor Imagery, [INFO.INFO-HC] Computer Science [cs]/Human-Computer Interaction [cs.HC], Event-Related Desynchronization, Users Profiling, [STAT.ML] Statistics [stat]/Machine Learning [stat.ML]

Dateibeschreibung: application/pdf

Zugangs-URL: https://inria.hal.science/hal-04981146v1
https://doi.org/10.1109/bci65088.2025.10931645
https://inria.hal.science/hal-04981146v1/document

Predicting Workload in Virtual Flight Simulations Using EEG Spectral and Connectivity Features

Autoren: Verkennis, Bas Van Weelden, Evy Marogna, Francesca L. et al.

Quelle: 2025 IEEE International Conference on Artificial Intelligence and eXtended and Virtual Reality (AIxVR). :82-89

Schlagwörter: Cognitive Workload, NASA Task Load Index (NASA-TLX), Phase-Locking Value (PLV), Flight Simulation, Electroen-cephalogram (EEG), Brain-Computer Interface (BCI), Virtual Reality (VR), Functional Connectivity

Zugangs-URL: https://hdl.handle.net/1871.1/19726d37-49ac-4242-9121-33cad14af896
https://research.vu.nl/en/publications/19726d37-49ac-4242-9121-33cad14af896
https://doi.org/10.1109/AIxVR63409.2025.00019