Machine-learning-based coadaptive calibration for brain-computer interfaces.
about
Brain computer interfaces, a review.Using reinforcement learning to provide stable brain-machine interface control despite neural input reorganizationFirst Steps Toward a Motor Imagery Based Stroke BCI: New Strategy to Set up a Classifier.Online adaptation of a c-VEP Brain-computer Interface(BCI) based on error-related potentials and unsupervised learning.Fast mental states decoding in mixed realitySelective sensation based brain-computer interface via mechanical vibrotactile stimulationBrain-computer interfacing using modulations of alpha activity induced by covert shifts of attention.Predicting BCI subject performance using probabilistic spatio-temporal filters.Large-Scale Assessment of a Fully Automatic Co-Adaptive Motor Imagery-Based Brain Computer Interface.Distributed cortical adaptation during learning of a brain-computer interface task.Near-infrared spectroscopy (NIRS)-based eyes-closed brain-computer interface (BCI) using prefrontal cortex activation due to mental arithmetic.Brain-computer interfaces: a powerful tool for scientific inquiry.Toward an Open-Ended BCI: A User-Centered Coadaptive Design.Unsupervised adaptation of brain-machine interface decoders.Decoding finger movement in humans using synergy of EEG cortical current signals.Facilitating motor imagery-based brain-computer interface for stroke patients using passive movement.Flaws in current human training protocols for spontaneous Brain-Computer Interfaces: lessons learned from instructional design.Robust common spatial filters with a max-min approach.Recursive Exponentially Weighted N-way Partial Least Squares Regression with Recursive-Validation of Hyper-Parameters in Brain-Computer Interface Applications.Adaptive classification on brain-computer interfaces using reinforcement signals.Adaptive multiclass classification for brain computer interfaces.Discriminative learning of propagation and spatial pattern for motor imagery EEG analysis.EEG data space adaptation to reduce intersession nonstationarity in brain-computer interface.Eyes-closed hybrid brain-computer interface employing frontal brain activation.The Cybathlon BCI race: Successful longitudinal mutual learning with two tetraplegic users.Improvement of Information Transfer Rates Using a Hybrid EEG-NIRS Brain-Computer Interface with a Short Trial Length: Offline and Pseudo-Online Analyses.Effects of Luminosity Contrast and Stimulus Duration on User Performance and Preference in a P300-Based Brain–Computer InterfaceComparison of EEG measurement of upper limb movement in motor imagery training system
P2860
Q26995073-4143A430-B0A2-4011-84FE-8AB11F806E5EQ27324955-C897C884-24D7-4F4B-90E0-00233B0ECAE7Q30474761-28EAF411-90E7-407A-B3BF-872B9ED0DE4EQ34510735-2BFB110B-1908-458E-93A1-DA37EB85F5E6Q34579603-F0DAD121-1260-4F5B-B6CE-E15D5FEA6B95Q34769462-4B68E971-19C7-4665-9F7E-ACCFF78D97E3Q35044403-E1C4B5C1-C82B-4181-AD14-E607A2CFD78AQ35097242-47E19C70-76D2-43C9-943C-16A2A72FA985Q35927543-F36CE19B-F695-4A38-B51D-BF2DFF5448E9Q36967795-69E1F5CF-A840-49AE-A1BE-39390D7538D0Q37400239-C5E21CAC-22EC-42C3-807B-B2EAC73F19C9Q38202802-87457EE9-E031-47F3-BF2D-4B3CDF3733BFQ38646787-D0BFDD72-32DA-46B3-B8DB-1D8F69CF02FAQ41110737-118E2E32-A7F2-4161-827D-34B9CFA5FF8AQ41200615-C6B2C8B6-AFBC-4428-BA8B-6C8781D587EDQ42369737-217CCF00-B61E-496D-BFE6-7691C31F7FD2Q42626341-C0A22A75-82C5-4C1A-AC69-EAA84C9BE075Q45397391-4029D967-ACB8-4D6C-9E8F-85D434BCBCDDQ47107253-274E8741-0336-4B7E-BF25-BFD46ADC9663Q47325315-AB8CD242-878A-4996-8760-933320DD8198Q50673918-278CD751-1ED8-452C-86CA-D3C56063E04BQ50731463-E86209EE-57FA-45FC-B386-24C6A8A5AF02Q51219755-C94CE3B1-BB0A-4E29-AC2A-ED8A41DA1FCFQ55241198-C066AF02-D610-4E28-8141-43EAAF7520F3Q55388089-F0D0F972-3E72-4406-AABA-4059BBA02465Q55452113-4E3A7419-8336-4718-B76F-52CFF4899D80Q57443523-51E64574-AA81-44F4-B6F4-2CE4C354AC5EQ58803924-F2521D10-2FD2-4D8A-8938-B14BE431DAA3
P2860
Machine-learning-based coadaptive calibration for brain-computer interfaces.
description
2010 nî lūn-bûn
@nan
2010年の論文
@ja
2010年学术文章
@wuu
2010年学术文章
@zh-cn
2010年学术文章
@zh-hans
2010年学术文章
@zh-my
2010年学术文章
@zh-sg
2010年學術文章
@yue
2010年學術文章
@zh
2010年學術文章
@zh-hant
name
Machine-learning-based coadaptive calibration for brain-computer interfaces.
@en
Machine-learning-based coadaptive calibration for brain-computer interfaces.
@nl
type
label
Machine-learning-based coadaptive calibration for brain-computer interfaces.
@en
Machine-learning-based coadaptive calibration for brain-computer interfaces.
@nl
prefLabel
Machine-learning-based coadaptive calibration for brain-computer interfaces.
@en
Machine-learning-based coadaptive calibration for brain-computer interfaces.
@nl
P2093
P2860
P356
P1433
P1476
Machine-learning-based coadaptive calibration for brain-computer interfaces.
@en
P2093
Benjamin Blankertz
Carmen Vidaurre
Claudia Sannelli
P2860
P304
P356
10.1162/NECO_A_00089
P577
2010-12-16T00:00:00Z