about
On the applicability of brain reading for predictive human-machine interfaces in roboticsBrain-computer interface based on generation of visual imagesTranslation of EEG spatial filters from resting to motor imagery using independent component analysisA collaborative brain-computer interface for improving human performanceThe Berlin Brain-Computer Interface: Non-Medical Uses of BCI Technology.Development of speech prostheses: current status and recent advances.A bayesian model for exploiting application constraints to enable unsupervised training of a P300-based BCILearning from label proportions in brain-computer interfaces: Online unsupervised learning with guaranteesTrue zero-training brain-computer interfacing--an online study.A review of brain-computer interface games and an opinion survey from researchers, developers and users.Whatever works: a systematic user-centered training protocol to optimize brain-computer interfacing individually.Real-time state estimation in a flight simulator using fNIRS.A comparison of univariate, vector, bilinear autoregressive, and band power features for brain-computer interfaces.Leveraging anatomical information to improve transfer learning in brain-computer interfaces.A Fully Automated Trial Selection Method for Optimization of Motor Imagery Based Brain-Computer Interface.High-speed spelling with a noninvasive brain-computer interface.Autonomous Parameter Adjustment for SSVEP-Based BCIs with a Novel BCI WizardAssisted closed-loop optimization of SSVEP-BCI efficiency.Detection of movement-related cortical potentials based on subject-independent trainingPre-Trial EEG-Based Single-Trial Motor Performance Prediction to Enhance Neuroergonomics for a Hand Force TaskAn Intelligent Man-Machine Interface-Multi-Robot Control Adapted for Task Engagement Based on Single-Trial Detectability of P300.Robust single trial identification of conscious percepts triggered by sensory events of variable saliency.Affective Aspects of Perceived Loss of Control and Potential Implications for Brain-Computer Interfaces.Regularized common spatial patterns with subject-to-subject transfer of EEG signals.Grand challenges of brain computer interfaces in the years to come.Facilitating motor imagery-based brain-computer interface for stroke patients using passive movement.An Adaptive Calibration Framework for mVEP-Based Brain-Computer Interface.Multiclass Informative Instance Transfer Learning Framework for Motor Imagery-Based Brain-Computer Interface.
P2860
Q21090672-A6EFB4BB-25C1-485B-9CC5-48E7CA2A314FQ21135351-BC572313-4C6A-48F9-90B9-E8484A179796Q28729114-42A602C4-164B-4CDA-84C9-69ED43F23CCFQ28744129-6096ADE7-BAA4-4D16-9186-09B96B84525DQ28744182-D6B35CE7-9370-4CEE-BFEA-4113B341E4E8Q30474923-F577AB53-C6A1-487D-BDE2-22DE1060DA06Q30512712-4ABE4A08-05A8-4FAF-A324-C3931DCD0E45Q33563131-30BE2DFB-2396-43C0-A49F-200AD972D88EQ33960523-C36FF2A4-E00E-446B-9307-24C88AB50721Q34262655-EB88A0EF-A220-4FD2-BD9E-ACE752F62A2FQ35006245-2BF664FE-1F19-412F-80DA-00F603B8C323Q35225384-AD80C605-A354-4C71-B7C1-1E6BDC888879Q35529385-27FE670D-7466-46B8-B244-E294303176ECQ35925370-AB55FC52-1EC3-4731-A158-F11A3F48CDC9Q36134255-BE897244-3FD7-45F9-A7AB-1B0D50F11DE8Q36268624-72668F10-25E6-4CDC-A44A-02A0DFC2DAAFQ36392259-863483DB-DEAF-4570-872A-505FAC836D01Q36634447-E9BC9544-1212-4D5C-8C3B-FB402CBEF23CQ36767850-846830E3-3809-4AB0-AFE0-1CDB4F9A2561Q36832115-A5674008-1C60-4A0D-9780-19FE1442DF0BQ37022845-ABEF0046-5A88-44DE-9F1D-51BE2F0CE6F4Q37509924-B95880C3-2D4C-43DC-BB89-6183D0D02A6DQ38645688-F77C7C1C-361B-40A0-915A-5E2FF32A09F0Q38872411-9922B872-1A96-411F-8098-E2D62B4E29CCQ41831601-00F45FA1-FB69-4D32-9D94-A2C9E8A5ABC4Q42369737-E3B78F03-4822-443D-B622-AC155A1FD2F5Q52571344-9217EB25-C350-4761-A8C3-A0848E17A981Q55044863-03E74DB3-D199-4CFD-ABF3-BA94FC4A98AD
P2860
description
2008 nî lūn-bûn
@nan
2008 թուականի Օգոստոսին հրատարակուած գիտական յօդուած
@hyw
2008 թվականի օգոստոսին հրատարակված գիտական հոդված
@hy
2008年の論文
@ja
2008年論文
@yue
2008年論文
@zh-hant
2008年論文
@zh-hk
2008年論文
@zh-mo
2008年論文
@zh-tw
2008年论文
@wuu
name
Towards zero training for brain-computer interfacing.
@ast
Towards zero training for brain-computer interfacing.
@en
type
label
Towards zero training for brain-computer interfacing.
@ast
Towards zero training for brain-computer interfacing.
@en
prefLabel
Towards zero training for brain-computer interfacing.
@ast
Towards zero training for brain-computer interfacing.
@en
P2860
P50
P1433
P1476
Towards zero training for brain-computer interfacing.
@en
P2093
Matthias Krauledat
P2860
P356
10.1371/JOURNAL.PONE.0002967
P407
P577
2008-08-13T00:00:00Z