2020
DOI: 10.1186/s40708-020-00105-1
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Abstract: Epilepsy is a serious chronic neurological disorder, can be detected by analyzing the brain signals produced by brain neurons. Neurons are connected to each other in a complex way to communicate with human organs and generate signals. The monitoring of these brain signals is commonly done using Electroencephalogram (EEG) and Electrocorticography (ECoG) media. These signals are complex, noisy, non-linear, non-stationary and produce a high volume of data. Hence, the detection of seizures and discovery of the bra… Show more

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Cited by 223 publications
(102 citation statements)
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“…Many studies on the nonlinear analysis of EEG and epilepsy have been reported, including reviews concerning ictal EEG detection and machine leaning approaches. [14][15][16] Ideally, interictal EEG with no paroxysmal abnormalities should be used to diagnose epilepsy and comorbid psychiatric disorders by using computerized analysis rather than expert observation and interpretation.…”
Section: Epilepsy and Nonlinear Eeg Analysismentioning
confidence: 99%
“…Many studies on the nonlinear analysis of EEG and epilepsy have been reported, including reviews concerning ictal EEG detection and machine leaning approaches. [14][15][16] Ideally, interictal EEG with no paroxysmal abnormalities should be used to diagnose epilepsy and comorbid psychiatric disorders by using computerized analysis rather than expert observation and interpretation.…”
Section: Epilepsy and Nonlinear Eeg Analysismentioning
confidence: 99%
“…As a result, obesity is a significantly contributes in morbidity and mortality rates [68]. For this, public awareness at primary level is mandatory like other diseases [70,71,72] for the interventions to prevent the environment from overweight or obesity. Secondary, if the overweight is found promote the weight loss methods in society, excess exercise and aware them to be away from sedentary lifestyle and proper prescribed lifestyle management should be adopted.…”
Section: Trends Obtained From Bmi ≥ 40mentioning
confidence: 99%
“…Recently, artificial intelligence and machine learning techniques also including deep-learning methods have been applied to support the feature extraction and classification, Refs. [ 92 , 93 , 94 ]. Moreover, the success of advanced AI and deep-learning algorithms in epilepsy detection has opened the way to epilepsy prediction, where interictal signals that are observed between seizures are studied with the aim of extracting reliable markers of a future seizure [ 95 ].…”
Section: Neural Recording Circuit Techniquesmentioning
confidence: 99%