Integrated CWT-CNN for Epilepsy Detection Using Multiclass EEG Dataset
نویسندگان
چکیده
منابع مشابه
Feature Selection for Epilepsy Detection Using Eeg
EEG signal when decomposed into frequency subbands, gives us several statistical features in each band. Some of these features that may be employed for detection of epilepsy are explored in this paper.
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ABSTRACT Brain is the most complex organ amongst all the systems in human body. ElectroEncephaloGraph EEG is a technique which is used to identify the neurological disorder of brain. Epilepsy is one of the most common neurological disorders of brain. Epilepsy needs to be detected efficiently using required EEG feature extraction such as: variance, power spectral density, energy and entropy. Thi...
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Epilepsy Detection using EEG requires feature extraction from the acquired signal in specific frequency range of delta, theta, alpha, beta, and gamma. Though some researchers have mentioned the use of DWT decomposition to obtain these bands, the method given is inadequate to achieve these. This paper explicitly describes the method of up-sampling and recombining of several decomposed subbands t...
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ژورنال
عنوان ژورنال: Computers, Materials & Continua
سال: 2021
ISSN: 1546-2226
DOI: 10.32604/cmc.2021.018239