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Adaptive Filtering for Epileptic Event Detection in the EEG
(Institute of Biomedical Engineering, 2019-12)
Purpose The development of online seizure detection techniques as well as prediction methods are very critical. Patient quality of life could improve signifcantly if the beginning of a seizure could be predicted or detected ...
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 ...
An EEG Signal Recognition Algorithm During Epileptic Seizure Based on Distributed Edge Computing
Epilepsy is one kind of brain diseases, and its sudden unpredictability is the main cause of disability and even death. Thus, it is of great significance to identify electroencephalogram (EEG) during the seizure quickly ...
Order/disorder in brain electrical activity
(Revista Mexicana de Física, 2009)
Selecting Statistical Characteristics of Brain Signals to Detect Epileptic Seizures using Discrete Wavelet Transform and Perceptron Neural Network
Electroencephalogram signals (EEG) have always been used in medical diagnosis. Evaluation of the statistical characteristics of EEG signals is actually the foundation of all brain signal processing methods. Since the correct ...
A quantitative analysis of an EEG epileptic record based on multiresolution wavelet coefficients
(Molecular Diversity Preservation International, 2014-11)
The characterization of the dynamics associated with electroencephalogram (EEG) signal combining an orthogonal discrete wavelet transform analysis with quantifiers originated from information theory is reviewed. In addition, ...
Fast statistical model-based classification of epileptic EEG signals
(Elsevier, 2018-01)
This paper presents a supervised classification method to accurately detect epileptic brain activity in real-time from electroencephalography (EEG) data. The proposed method has three main strengths: it has low computational ...