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Nonlinear analysis of the electroencephalogram in depth of anesthesia
(Revista Facultad de Ingenieria Universidad de Antioquia, 2015-02-09)
Digital signal processing of the electroencephalogram (EEG) became important in monitoring depth of anesthesia (DoA) being used to provide a better anesthetic technique. The objective of this work was to conduct a review ...
Classificação de estágios de sono através da aplicação de transformada wavelet discreta sobre um único canal de eletroencefalograma
(Universidade Federal de Santa MariaBrasilCiência da ComputaçãoUFSMPrograma de Pós-Graduação em Ciência da ComputaçãoCentro de Tecnologia, 2016-01-25)
The correct sleep stage classification allows sleep experts to diagnose and treat disorders
such as apnea, narcolepsy and insomnia. Such task is classically performed by sleep
medicine experts, where one or more physiological ...
Electroencephalogram Signal Classification Based On Shearlet And Contourlet Transforms
(Pergamon-Elsevier Science LTDOxford, 2017)
EEG-based person identification through Binary Flower Pollination Algorithm
(Elsevier B.V., 2016-11-15)
Electroencephalogram (EEG) signal presents a great potential for highly secure biometric systems due to its characteristics of universality, uniqueness, and natural robustness to spoofing attacks. EEG signals are measured ...
Automatic identification of epileptic EEG signals through binary magnetic optimization algorithms
(2017-06-28)
Epilepsy is a class of chronic neurological disorders characterized by transient and unexpected electrical disturbances of the brain. The automated analysis of the electroencephalogram (EEG) signal can be instrumental for ...
Affective recognition from EEG signals: an integrated data-mining approach
(Journal of Ambient Intelligence and Humanized Computing, 2018)
Envelope analysis links oscillatory and arrhythmic EEG activities to two types of neuronal synchronization
(Academic Press INC Elsevier Science, 2018)
Traditionally, EEG is understood as originating from the synchronous activation of neuronal populations that generate rhythmic oscillations in specific frequency bands. Recently, new neuronal dynamics regimes have been ...
Electroencephalogram data platform for application of reduction methods
(Universidade Federal do Rio de JaneiroBrasilInstituto Alberto Luiz Coimbra de Pós-Graduação e Pesquisa de EngenhariaPrograma de Pós-Graduação em Engenharia BiomédicaUFRJ, 2020)
Evaluation of electroencephalogram source localization methods for the decoding of motor information
(Instituto Tecnológico y de Estudios Superiores de Monterrey, 2020-07)
There are several technologies in the world that start using brain signals as input, such as wheelchairs, gadjets, or prosthesis. This machines are known as brain-computer interfaces, which are systems that establish a ...
EEG signal processing in brain–computer interface
(Elsevier, 2018)
A brain–computer interface (BCI) system employs the electrical signals of the brain of the user to control a device according to the user’s intentions. Thus, the brain activity patterns should be identified by the system ...