Results 1 to 10 of about 133,886 (355)
Handbook of Clinical Neurology, 2020 The electroencephalogram (EEG) was invented almost 100 years ago and is still a method of choice for many research questions, even applications-from functional brain imaging in neuroscientific investigations during movement to real-time applications like
Gernot R. Müller-Putz
semanticscholar +7 more sources
Open Vocabulary Electroencephalography-To-Text Decoding and Zero-shot Sentiment Classification [PDF]
arXiv, 2021 State-of-the-art brain-to-text systems have achieved great success in decoding language directly from brain signals using neural networks. However, current approaches are limited to small closed vocabularies which are far from enough for natural communication. In addition, most of the high-performing approaches require data from invasive devices (e.g.,
Zhenhailong Wang, Heng Ji
arxiv +3 more sources
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
Hubert J. Banville +5 more
arxiv +3 more sources
Electroencephalography Today [PDF]
Journal of the Royal Society of Medicine, 1979 E. M. R. Critchley
+13 more sources
Electroencephalography Today [PDF]
Journal of the Royal Society of Medicine, 1978 E. M. R. Critchley
+10 more sources
Electroencephalography source localization [PDF]
Clinical and Experimental Pediatrics, 2023 Electroencephalography (EEG) has been and is still widely used in brain function research. EEG has advantages over other neuroimaging modalities. First, it not only directly images the electrical activity of neurons; it has a higher temporal resolution ...
Tae-Hoon Eom
doaj +1 more source
Continuous heart rate variability and electroencephalography monitoring in severe acute brain injury: a preliminary study [PDF]
Acute and Critical Care, 2021 Background Decreases in heart rate variability have been shown to be associated with poor outcomes in severe acute brain injury. However, it is unknown whether the changes in heart rate variability precede neurological deterioration in such patients.
Hyunjo Lee +2 more
doaj +1 more source
Italian National Conference on Sensors, 2023 The electroencephalography (EEG) signal is a noninvasive and complex signal that has numerous applications in biomedical fields, including sleep and the brain–computer interface.
A. Chaddad +3 more
semanticscholar +1 more source
Considerate motion imagination classification method using deep learning.
PLoS ONE, 2022 In order to improve the classification accuracy of motion imagination, a considerate motion imagination classification method using deep learning is proposed.
Zhaokun Yan, Xiangquan Yang, Yu Jin
doaj +2 more sources
The International Cardiac Arrest Research Consortium Electroencephalography Database
Critical Care Medicine, 2023 OBJECTIVES: To develop the International Cardiac Arrest Research (I-CARE), a harmonized multicenter clinical and electroencephalography database for acute hypoxic-ischemic brain injury research involving patients with cardiac arrest.
MD Edilberto Amorim +16 more
semanticscholar +1 more source