Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Rob Zink"'
Publikováno v:
Journal of neural engineering. 18(5)
OBJECTIVE: Unobtrusive EEG monitoring in everyday life requires the availability of highly miniaturized EEG devices (mini-EEGs), which ideally consist of a wireless node with a small scalp area footprint, in which the electrodes, amplifier and wirele
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8177e1699b2e44f60065c2ee3fcfb2d4
https://pubmed.ncbi.nlm.nih.gov/34517358
https://pubmed.ncbi.nlm.nih.gov/34517358
Autor:
Patrick Dupont, Sabine Deprez, Lieven Lagae, Kristel Van Calsteren, Ivan Myatchin, Tineke Vandenbroucke, Frédéric Amant, Rob Zink, Charlotte Sleurs, Jeroen Blommaert
Publikováno v:
Clinical neurophysiology, 130(9), 1655-1664. Elsevier Ireland Ltd
Clinical Neurophysiology
Clinical Neurophysiology
OBJECTIVE This study examines the long-term impact of prenatal exposure to chemotherapy on executive functioning and the contribution of late-prematurity to this effect, using event- related potentials. METHODS Mothers of the prenatal-exposed childre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8b8b8480b77db85311eef44a891eac56
https://lirias.kuleuven.be/handle/123456789/638961
https://lirias.kuleuven.be/handle/123456789/638961
Publikováno v:
DSW
The fourth release of Tensorlab — a Matlab toolbox which bundles state-of-the-art tensor algorithms and tools — introduces a number of algorithms which allow a variety of new types of problems to be solved. For example, Gauss–Newton type algori
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::79b098ea0edf4e586958f49552cc3283
https://lirias.kuleuven.be/handle/123456789/636972
https://lirias.kuleuven.be/handle/123456789/636972
Auditory attention detection (AAD) is promising for use in auditory-assistive devices to detect to which sound the user is attending. Being able to train subjects in achieving high AAD performance would greatly increase its application potential. In
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::354bb6857121faf2063aa6682ada88de
https://doi.org/10.1101/218727
https://doi.org/10.1101/218727
Publikováno v:
Proceedings of the International Scientific Conference - Sinteza 2017.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cbb577120a87aaa7517ae3d6801232ac
https://doi.org/10.15308/sinteza-2017-9-18
https://doi.org/10.15308/sinteza-2017-9-18
OBJECTIVE: In the past few years there has been a growing interest in studying brain functioning in natural, real-life situations. Mobile EEG allows to study the brain in real unconstrained environments but it faces the intrinsic challenge that it is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2e0fd437ea458e1fadb443bdf9d5dca4
https://lirias.kuleuven.be/handle/123456789/545090
https://lirias.kuleuven.be/handle/123456789/545090
Publikováno v:
Journal of neural engineering. 13(2)
OBJECTIVE: One of the major drawbacks in EEG brain-computer interfaces (BCI) is the need for subject-specific training of the classifier. By removing the need for a supervised calibration phase, new users could potentially explore a BCI faster. In th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5d8d336309fe6760997880d60527b941
https://pubmed.ncbi.nlm.nih.gov/26824883
https://pubmed.ncbi.nlm.nih.gov/26824883
Publikováno v:
EMBC
One of the major drawbacks in mobile EEG Brain Computer Interfaces (BCI) is the need for subject specific training data to train a classifier. By removing the need for supervised classification and calibration phase, new users could start immediate i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0f2e9cde906a7fd5a5b909ab5df6821c
https://doi.org/10.1109/embc.2015.7318723
https://doi.org/10.1109/embc.2015.7318723
Publikováno v:
NER
© 2015 IEEE. The analysis of mobile EEG Brain Computer Interface (BCI) recordings can benefit from unsupervised learning methods. Removing the calibration phase allows for faster and shorter interactions with a BCI and could potentially deal with no
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a520d0a0c3623204044cfd1c183a1568
https://doi.org/10.1109/ner.2015.7146558
https://doi.org/10.1109/ner.2015.7146558
Publikováno v:
EMBC
In the past decade, technological advances have made it possible to reliably measure brain activity using simultaneous EEG-fMRI recordings inside an MR scanner. The main challenge then became to investigate the coupling between the EEG and fMRI signa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e4c931b61cb7b00265d145f2b6e04277
https://pubmed.ncbi.nlm.nih.gov/24111113
https://pubmed.ncbi.nlm.nih.gov/24111113