Electroencephalography signal processing based on textural features for monitoring the driver's state by a Brain-Computer Interface [PDF]
arXiv, 2020 In this study we investigate a textural processing method of electroencephalography (EEG) signal as an indicator to estimate the driver's vigilance in a hypothetical Brain-Computer Interface (BCI) system. The novelty of the solution proposed relies on employing the one-dimensional Local Binary Pattern (1D-LBP) algorithm for feature extraction from pre ...
arxiv
Advances in human intracranial electroencephalography research, guidelines and good practices
NeuroImage, 2022 M. Mercier +26 more
semanticscholar +1 more source
STUDIES ON NITROUS OXIDE, MEPERIDINE AND LEVALLORPHAN WITH UNIPOLAR ELECTROENCEPHALOGRAPHY [PDF]
, 1957 W. CURTIS PEARCY +2 more
openalex +1 more source
Self-supervised representation learning from electroencephalography signals [PDF]
arXiv, 2019 The supervised learning paradigm is limited by the cost - and sometimes the impracticality - of data collection and labeling in multiple domains. Self-supervised learning, a paradigm which exploits the structure of unlabeled data to create learning problems that can be solved with standard supervised approaches, has shown great promise as a pretraining
arxiv
QUANTITATIVE ELECTROENCEPHALOGRAPHY IN MAN AS A MEASURE OF CNS STIMULATION* [PDF]
, 1963 Leonide Goldstein +2 more
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Single-channel electroencephalography decomposition by detector-atom network and its pre-trained model [PDF]
arXivThis paper presents a novel single-channel decomposition approach to facilitate the decomposition of electroencephalography (EEG) signals recorded with limited channels. Our model posits that an EEG signal comprises short, shift-invariant waves, referred to as atoms. We design a decomposer as an artificial neural network aimed at estimating these atoms
arxiv
Estimating Visual Comfort in Stereoscopic Displays Using Electroencephalography: A Proof-of-Concept [PDF]
arXiv, 2015 With stereoscopic displays, a depth sensation that is too strong could impede visual comfort and result in fatigue or pain. Electroencephalography (EEG) is a technology which records brain activity. We used it to develop a novel brain-computer interface that monitors users' states in order to reduce visual strain.
arxiv
Diagnosis of Alzheimer’s disease with Electroencephalography in a differential framework
PLoS ONE, 2018 This study addresses the problem of Alzheimer’s disease (AD) diagnosis with Electroencephalography (EEG). The use of EEG as a tool for AD diagnosis has been widely studied by comparing EEG signals of AD patients only to those of healthy subjects.
N. Houmani +6 more
semanticscholar +1 more source