Mobile EEG on the bike: disentangling attentional and physical contributions to auditory attention tasks
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Sabine Van Huffel | Maarten De Vos | Borbála Hunyadi | Rob Zink | S. Huffel | M. Vos | B. Hunyadi | Rob Zink
[1] M. De Vos,et al. Removing muscle and eye artifacts using blind source separation techniques in ictal EEG source imaging , 2009, Clinical Neurophysiology.
[2] Yu-Kai Chang,et al. Neurophysiological and behavioral correlates of cognitive control during low and moderate intensity exercise , 2016, NeuroImage.
[3] Michel J A M van Putten,et al. Mobile EEG in epilepsy. , 2014, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.
[4] Wim Van Paesschen,et al. Canonical Correlation Analysis Applied to Remove Muscle Artifacts From the Electroencephalogram , 2006, IEEE Transactions on Biomedical Engineering.
[5] Caterina Pesce,et al. Antecedent acute cycling exercise affects attention control: an ERP study using attention network test , 2015, Front. Hum. Neurosci..
[6] S. Schneider,et al. Neuroelectric adaptations to cognitive processing in virtual environments: an exercise-related approach , 2015, Experimental Brain Research.
[7] Fabien Lotte,et al. Brain-Computer Interfaces: Beyond Medical Applications , 2012, Computer.
[8] Arnaud Delorme,et al. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis , 2004, Journal of Neuroscience Methods.
[9] Febo Cincotti,et al. Out of the frying pan into the fire--the P300-based BCI faces real-world challenges. , 2011, Progress in brain research.
[10] Tamara G. Kolda,et al. Tensor Decompositions and Applications , 2009, SIAM Rev..
[11] M Congedo,et al. A review of classification algorithms for EEG-based brain–computer interfaces , 2007, Journal of neural engineering.
[12] Andrzej Cichocki,et al. Tensor Decompositions for Signal Processing Applications: From two-way to multiway component analysis , 2014, IEEE Signal Processing Magazine.
[13] Maarten De Vos,et al. Let's face it, from trial to trial: Comparing procedures for N170 single-trial estimation , 2012, NeuroImage.
[14] N. Birbaumer,et al. An auditory oddball brain–computer interface for binary choices , 2010, Clinical Neurophysiology.
[15] Sabine Van Huffel,et al. Removal of Muscle Artifacts from EEG Recordings of Spoken Language Production , 2010, Neuroinformatics.
[16] Daniel P. Ferris,et al. Removal of movement artifact from high-density EEG recorded during walking and running. , 2010, Journal of neurophysiology.
[17] Alexander J. Casson,et al. Towards out-of-the-lab EEG in uncontrolled environments: Feasibility study of dry EEG recordings during exercise bike riding , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
[18] Fumikazu Miwakeichi,et al. Decomposing EEG data into space–time–frequency components using Parallel Factor Analysis , 2004, NeuroImage.
[19] Klaus-Robert Müller,et al. True Zero-Training Brain-Computer Interfacing – An Online Study , 2014, PloS one.
[20] H. Flor,et al. A spelling device for the paralysed , 1999, Nature.
[21] Maarten De Vos,et al. P300 speller BCI with a mobile EEG system: comparison to a traditional amplifier , 2014, Journal of neural engineering.
[22] Ronald N. Goodman,et al. Neural decoding of treadmill walking from noninvasive electroencephalographic signals. , 2011, Journal of neurophysiology.
[23] Thierry Dutoit,et al. A P300-based Quantitative Comparison between the Emotiv Epoc Headset and a Medical EEG Device , 2012, BioMed 2012.
[24] E. Basar,et al. Wavelet analysis of oddball P300. , 2001, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.
[25] N. Birbaumer,et al. An auditory oddball (P300) spelling system for brain-computer interfaces. , 2009, Psychophysiology.
[26] Trevor Thompson,et al. EEG applications for sport and performance. , 2008, Methods.
[27] T. Jung,et al. Assessing the feasibility of online SSVEP decoding in human walking using a consumer EEG headset , 2014, Journal of NeuroEngineering and Rehabilitation.
[28] Sabine Van Huffel,et al. Tensor-based classification of an auditory mobile BCI without a subject-specific calibration phase. , 2016, Journal of neural engineering.
[29] Martin G Bleichner,et al. Exploring miniaturized EEG electrodes for brain-computer interfaces. An EEG you do not see? , 2015, Physiological reports.
[30] G. Cheron,et al. About the cortical origin of the low-delta and high-gamma rhythms observed in EEG signals during treadmill walking , 2014, Neuroscience Letters.
[31] Stefan Haufe,et al. On the interpretation of weight vectors of linear models in multivariate neuroimaging , 2014, NeuroImage.
[32] Wojciech Samek,et al. Investigating effects of different artefact types on motor imagery BCI , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
[33] Rasmus Bro,et al. Multiway analysis of epilepsy tensors , 2007, ISMB/ECCB.
[34] Maureen Clerc,et al. Electroencephalography (EEG)‐Based Brain–Computer Interfaces , 2015 .
[35] Guillaume Gibert,et al. OpenViBE: An Open-Source Software Platform to Design, Test, and Use BrainComputer Interfaces in Real and Virtual Environments , 2010, PRESENCE: Teleoperators and Virtual Environments.
[36] T. Vaughan,et al. Toward independent home use of brain-computer interfaces: a decision algorithm for selection of potential end-users. , 2015, Archives of physical medicine and rehabilitation.
[37] Richard A. Harshman,et al. Foundations of the PARAFAC procedure: Models and conditions for an "explanatory" multi-model factor analysis , 1970 .
[38] Björn Eskofier,et al. Comparison of the AMICA and the InfoMax algorithm for the reduction of electromyogenic artifacts in EEG data , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
[39] J Spinnato,et al. Detecting single-trial EEG evoked potential using a wavelet domain linear mixed model: application to error potentials classification , 2015, Journal of neural engineering.
[40] Alexandre Barachant,et al. A Plug&Play P300 BCI Using Information Geometry , 2014, ArXiv.
[41] Stephanie Brandl,et al. Bringing BCI into everyday life: Motor imagery in a pseudo realistic environment , 2015, 2015 7th International IEEE/EMBS Conference on Neural Engineering (NER).
[42] Jeanick Brisswalter,et al. Effects of long duration exercise on cognitive function, blood glucose, and counterregulatory hormones in male cyclists , 2004, Neuroscience Letters.
[43] Scott E. Kerick,et al. Assessment of EEG Signal Quality in Motion Environments , 2009 .
[44] A. Engel,et al. Auditory novelty oddball allows reliable distinction of top-down and bottom-up processes of attention. , 2002, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.
[45] Daniel P Ferris,et al. Isolating gait-related movement artifacts in electroencephalography during human walking , 2015, Journal of neural engineering.
[46] P. Aspinall,et al. The urban brain: analysing outdoor physical activity with mobile EEG , 2013, British Journal of Sports Medicine.
[47] Kelvin S. Oie,et al. Cognition in action: imaging brain/body dynamics in mobile humans , 2011, Reviews in the neurosciences.
[48] Vinzenz von Tscharner,et al. Methodological aspects of EEG and body dynamics measurements during motion , 2014, Front. Hum. Neurosci..
[49] Wojciech Samek,et al. Transferring Subspaces Between Subjects in Brain--Computer Interfacing , 2012, IEEE Transactions on Biomedical Engineering.
[50] Thierry Dutoit,et al. Performance of the Emotiv Epoc headset for P300-based applications , 2013, Biomedical engineering online.
[51] Matthew B. Pontifex,et al. Neuroelectric and behavioral indices of interference control during acute cycling , 2007, Clinical Neurophysiology.
[52] Sabine Van Huffel,et al. Classifying the auditory P300 using mobile EEG recordings without calibration phase , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
[53] Stefan Haufe,et al. Single-trial analysis and classification of ERP components — A tutorial , 2011, NeuroImage.
[54] Stefan Debener,et al. Mobile EEG: towards brain activity monitoring during natural action and cognition. , 2014, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.
[55] S. Debener,et al. How about taking a low-cost, small, and wireless EEG for a walk? , 2012, Psychophysiology.
[56] Christian Jutten,et al. Multiclass Brain–Computer Interface Classification by Riemannian Geometry , 2012, IEEE Transactions on Biomedical Engineering.
[57] S. Debener,et al. Towards a truly mobile auditory brain-computer interface: exploring the P300 to take away. , 2014, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.
[58] W. Klimesch. EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis , 1999, Brain Research Reviews.
[59] Christian Kothe,et al. Towards passive brain–computer interfaces: applying brain–computer interface technology to human–machine systems in general , 2011, Journal of neural engineering.
[60] C. Askew,et al. Effects of Exercise in Immersive Virtual Environments on Cortical Neural Oscillations and Mental State , 2015, Neural plasticity.
[61] Gary H. Glover,et al. Grand Challenges in Mapping the Human Brain: NSF Workshop Report , 2013, IEEE Transactions on Biomedical Engineering.
[62] Michael E. Smith,et al. Monitoring Task Loading with Multivariate EEG Measures during Complex Forms of Human-Computer Interaction , 2001, Hum. Factors.
[63] J. Polich. Updating P300: An integrative theory of P3a and P3b , 2007, Clinical Neurophysiology.
[64] Scott Makeig,et al. BCILAB: a platform for brain–computer interface development , 2013, Journal of neural engineering.
[65] Liqing Zhang,et al. Noninvasive BCIs: Multiway Signal-Processing Array Decompositions , 2008, Computer.
[66] S. Debener,et al. Unobtrusive ambulatory EEG using a smartphone and flexible printed electrodes around the ear , 2015, Scientific Reports.
[67] A. Kübler,et al. Effects of training and motivation on auditory P300 brain–computer interface performance , 2016, Clinical Neurophysiology.
[68] Kerry L. Coburn,et al. Effects of aerobic exercise and gender on visual and auditory P300, reaction time, and accuracy , 1999, European Journal of Applied Physiology and Occupational Physiology.
[69] Julien Penders,et al. Wearable, Wireless EEG Solutions in Daily Life Applications: What are we Missing? , 2015, IEEE Journal of Biomedical and Health Informatics.
[70] Benjamin Schrauwen,et al. A Bayesian Model for Exploiting Application Constraints to Enable Unsupervised Training of a P300-based BCI , 2012, PloS one.
[71] T. Chau,et al. Effects of user mental state on EEG-BCI performance , 2015, Front. Hum. Neurosci..