| Mobile EEG on the bike: disentangling attentional and physical contributions to auditory attention tasks R Zink, B Hunyadi, S Van Huffel, M De Vos Journal of Neural Engineering 13 (4), 046017-046017, 2016 | 149 | 2016 |
| Online detection of auditory attention with mobile EEG: closing the loop with neurofeedback R Zink, S Proesmans, A Bertrand, S Van Huffel, M De Vos BioRxiv, 218727, 2017 | 50 | 2017 |
| Tensor-based classification of an auditory mobile BCI without a subject-specific calibration phase R Zink, B Hunyadi, S Van Huffel, M De Vos Journal of neural engineering 13 (2), 026005, 2016 | 29 | 2016 |
| EEG miniaturization limits for stimulus decoding with EEG sensor networks AM Narayanan, R Zink, A Bertrand Journal of Neural Engineering 18 (5), 056042, 2021 | 10 | 2021 |
| Long-term impact of prenatal exposure to chemotherapy on executive functioning: An ERP study J Blommaert, R Zink, S Deprez, I Myatchin, P Dupont, T Vandenbroucke, ... Clinical Neurophysiology 130 (9), 1655-1664, 2019 | 9 | 2019 |
| The quest for single trial correlations in multimodal EEG-fMRI data M De Vos, R Zink, B Hunyadi, B Mijovic, S Van Huffel, S Debener 2013 35th Annual International Conference of the IEEE Engineering in …, 2013 | 8 | 2013 |
| On-line detection of auditory attention in a neurofeedback application R Zink, A Baptist, A Bertrand, S Van Huffel, M De Vos Proc. 8th International Workshop on Biosignal Interpretation, 1-4, 2016 | 6 | 2016 |
| Classifying the auditory P300 using mobile EEG recordings without calibration phase R Zink, B Hunyadi, S Van Huffel, M De Vos 2015 37th Annual International Conference of the IEEE Engineering in …, 2015 | 4 | 2015 |
| Exploring CPD based unsupervised classification for auditory BCI with mobile EEG. R Zink, B Hunyadi, S Van Huffel, M De Vos Neural Engineering (NER), 2015 7th International IEEE/EMBS Conference on, 53-56, 2015 | 4 | 2015 |
| Alpha and low-beta oscillatory patterns extracted with Canonical Polyadic Decomposition relate to LDA classifier performance in real-life Mobile EEG R Zink, B Hunyadi, S Van Huffel, M De Vos Proc. 8th International Workshop on Biosignal Interpretation, 1-4, 2016 | 2 | 2016 |
| Recent Numerical and Conceptual Advances for Tensor Decompositions—A Preview of Tensorlab 4.0 N Vervliet, M Vandecappelle, M Boussé, R Zink, L De Lathauwer 2019 IEEE Data Science Workshop (DSW), 310-314, 2019 | 1 | 2019 |
| Data-Driven Clustering of P300 EEG Data Using Coupled Tensor Decompositions R Zink, B Hunyadi, M De Vos, S Van Huffel Sinteza 2017 - International Scientific Conference on Information Technology …, 2017 | 1 | 2017 |
| Fast, accurate, unsupervised, and time-adaptive EEG-based auditory attention decoding for neuro-steered hearing devices S Geirnaert, R Zink, T Francart, A Bertrand Brain-Computer Interface Research: A State-of-the-Art Summary 11, 29-40, 2024 | | 2024 |
| Longterm impact of prenatal exposure to chemotherapy on attentional neurodevelopment: an ERP study J Blommaert, R Zink, S Deprez, I Myatchin, P Dupont, T Vandenbroucke, ... OHBM annual meeting, Date: 2019/06/09-2019/06/13, Location: Rome, Italy, 2019 | | 2019 |
| An afternoon with Mobile EEG: natural activities at home R Zink, S Van Huffel, M De Vos | | 2018 |
| TENSORLAB 4.0–A PREVIEW M Vandecappelle, M Boussé, N Vervliet, M Vendeville, R Zink, ... Proc. 14th International Conference on Latent Variable Analysis and Signal …, 2018 | | 2018 |
| Mobile EEG and tensor approaches for auditory attention analysis in real-life R Zink KU Leuven, 2017 | | 2017 |
| This content has been downloaded from IOPscience. Please scroll down to see the full text. LN Coregliano, AA Razborov, R Zink, B Hunyadi, S Van Huffel | | |
| This content has been downloaded from IOPscience. Please scroll down to see the full text. OV Shulika, M Klymenko, I Sukhoivanov, BA Knyazev, GN Kulipanov, ... | | |
Sabine Van HuffelKU LeuvenEmail verificata su esat.kuleuven.be