The Berlin Brain-Computer Interface: EEG-based communication without subject training.
about
On the applicability of brain reading for predictive human-machine interfaces in roboticsEvolution of brain-computer interfaces: going beyond classic motor physiologySingle trial classification of motor imagination using 6 dry EEG electrodesPrediction of three-dimensional arm trajectories based on ECoG signals recorded from human sensorimotor cortexThe Smartphone Brain Scanner: A Portable Real-Time Neuroimaging SystemDecoding vowels and consonants in spoken and imagined words using electrocorticographic signals in humansTranslation of EEG spatial filters from resting to motor imagery using independent component analysisA brain-computer interface with vibrotactile biofeedback for haptic information.Decoding flexion of individual fingers using electrocorticographic signals in humans.Towards zero training for brain-computer interfacing.A Ternary Brain-Computer Interface Based on Single-Trial Readiness Potentials of Self-initiated Fine Movements: A Diversified Classification Scheme.Exploration of computational methods for classification of movement intention during human voluntary movement from single trial EEGBCI Competition IV - Data Set I: Learning Discriminative Patterns for Self-Paced EEG-Based Motor Imagery DetectionChallenges in clinical applications of brain computer interfaces in individuals with spinal cord injury.Single tap identification for fast BCI control.Decoding intention at sensorimotor timescales.Steering a tractor by means of an EMG-based human-machine interface.Stream-based Hebbian eigenfilter for real-time neuronal spike discriminationSteady-state movement related potentials for brain-computer interfacing.Brain-computer interface systems: progress and prospects.L1 norm based common spatial patterns decomposition for scalp EEG BCITemporal hemodynamic classification of two hands tapping using functional near-infrared spectroscopy.Advanced neurotechnologies for chronic neural interfaces: new horizons and clinical opportunities.Gamma band activity associated with BCI performance: simultaneous MEG/EEG study.Decoding individual finger movements from one hand using human EEG signals.An energy efficient compressed sensing framework for the compression of electroencephalogram signals.Combined Auditory and Vibrotactile Feedback for Human-Machine-Interface Control.Application of BCI systems in neurorehabilitation: a scoping review.Multisubject "Learning" for Mental Workload Classification Using Concurrent EEG, fNIRS, and Physiological Measures.A Hybrid FPGA-Based System for EEG- and EMG-Based Online Movement Prediction.Epidural electrocorticography of phantom hand movement following long-term upper-limb amputation.Error potential detection during continuous movement of an artificial arm controlled by brain-computer interface.Towards development of a 3-state self-paced brain-computer interfaceFlaws in current human training protocols for spontaneous Brain-Computer Interfaces: lessons learned from instructional design.High-resolution movement EEG classification.EEG Database of Seizure Disorders for Experts and Application Developers.How Electroencephalogram Reference Influences the Movement Readiness Potential?Electrode fusion for the prediction of self-initiated fine movements from single-trial readiness potentials.Brain-Computer Interfaces for Augmentative and Alternative Communication: A Tutorial.Examining sensory ability, feature matching and assessment-based adaptation for a brain-computer interface using the steady-state visually evoked potential.
P2860
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P2860
The Berlin Brain-Computer Interface: EEG-based communication without subject training.
description
2006 nî lūn-bûn
@nan
2006年の論文
@ja
2006年学术文章
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2006年学术文章
@zh-cn
2006年学术文章
@zh-hans
2006年学术文章
@zh-my
2006年学术文章
@zh-sg
2006年學術文章
@yue
2006年學術文章
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2006年學術文章
@zh-hant
name
The Berlin Brain-Computer Interface: EEG-based communication without subject training.
@en
The Berlin Brain-Computer Interface: EEG-based communication without subject training.
@nl
type
label
The Berlin Brain-Computer Interface: EEG-based communication without subject training.
@en
The Berlin Brain-Computer Interface: EEG-based communication without subject training.
@nl
prefLabel
The Berlin Brain-Computer Interface: EEG-based communication without subject training.
@en
The Berlin Brain-Computer Interface: EEG-based communication without subject training.
@nl
P2093
P1476
The Berlin Brain-Computer Interface: EEG-based communication without subject training.
@en
P2093
Benjamin Blankertz
Florian Losch
Gabriel Curio
Guido Dornhege
Matthias Krauledat
Volker Kunzmann
P304
P356
10.1109/TNSRE.2006.875557
P577
2006-06-01T00:00:00Z