This exercise summarizes the basic brain processes in sleep and the use of the EEG (electroencephalogram; "brain waves") to measure sleep stages. It includes the following topics: ! sleep as an active process and brain areas that turn it on ! the EEG: how it is recorded and what it shows about brain activity ! the EEG for the two basic kinds of sleep, slow wave sleep (SWS) and rapid eye movemen...

Determining the exact duration of seizure activity is an important factor for predicting the efficacy of electroconvulsive therapy (ECT). In most cases, seizure duration is estimated manually by observing the electroencephalogram (EEG) waveform. In this article, we propose a method based on sample entropy (SampEn) that automatically detects the termination time of an ECT-induced seizure. SampEn...

Epilepsy is a very common neurological disorder. Electroencephalogram (EEG) is the major diagnostic tool used for analyzing the human epileptic seizure activity and there is a strong need of an efficient automatic seizure detection using it to ease the diagnosis. This work aims at an automatic system for diagnosis of epilepsy. Here we extract some features like fractal dimensions, sample entrop...

In this paper, we investigate the dynamical properties of electroencephalogram (EEG) signals of humans in sleep. By using a modified random walk method, we demonstrate that scale-invariance is embedded in EEG signals after a detrending procedure is applied. Furthermore, we study the dynamical evolution of the probability density function (PDF) of the detrended EEG signals by nonextensive statis...

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, an extension of this methodology based on multiresolution quantities, called wavelet leaders, is presented. In particular, the temporal evolution of Shannon entropy and the...

Characterized by recurrent and rapid seizures, epilepsy is a great threat to the livelihood of the human beings. A significant clinical tool for the study, analysis and diagnosis of the epilepsy is electroencephalogram (EEG) .In this paper the high dimensional EEG data is reduced to a low dimension by techniques such as Independent Component Analysis (ICA) and Principal Component Analysis (PCA)...

In recent medical research, tremendous progress has been made in the application of deep learning (DL) techniques. This article systematically reviews how DL techniques have applied to electroencephalogram (EEG) data for diagnostic and predictive purposes conducting research on mental disorders. EEG-studies psychiatric diseases based ICD-10 or DSM-V classification that used either convolutional...

brain death is defined as the permanent, irreversible and concurrent loss of all brain and brain stem functions. brain death diagnosis is based on clinical criteria and it is not routine to use paraclinical studies. in some countries, electroencephalogram (eeg) is performed in all patients for the determination of brain death while there is some skepticism in relying on eeg as a confirmatory te...