This paper reports a new approach on identifying the individuality of persons by using parametric classification of multiple mental thoughts. In the approach, electroencephalogram (EEG) signals were recorded when the subjects were thinking of one or more (up to five) mental thoughts. Autoregressive features were computed from these EEG signals and classified by Linear Discriminant classifier. T...

Electroencephalography is a domain concerning recording and interpretation of the electroencephalogram. Electroencephalogram (EEG) is a record of the electric signal generated by the cooperative action of brain cells, or more precisely, the time course of extracellular field potentials generated by their synchronous action. Electroencephalogram derives from the Greek words enkephalo (brain) and...

This paper presents an adaptive filtering method to remove ocular artifacts in the electroencephalogram (EEG) records. The major concern in analyzing EEG signal is the presence of ocular artifacts in EEG records caused due to various factors. It is essential to design specific filters to remove the artifacts in EEG records. Here, we proposed an adaptive

The record of human brain neural activities, namely electroencephalogram (EEG), is generally known as a non-stationary and nonlinear signal. In many applications, it is useful to divide the EEGs into segments within which the signals can be considered stationary. Combination of empirical mode decomposition (EMD) and Hilbert transform, called Hilbert-Huang transform (HHT), is a new and powerful ...

Statement of the Problem: As you know, there exist two different states in brain’s mental activity: true and false. In recent years, a progressive method wavelet transformation electroencephalogram (EEG) has been developed, which enabled us to establish fundamental possibility direct objective registration human activity. Earlier, we created an experimental model software for recognizing false ...

The electroencephalogram (EEG) is the most common tool used in sleep research. This unit describes the methods for recording and analyzing the EEG. Detailed protocols describe recorder calibration, electrode application, EEG recording, and computer EEG analysis with power spectral analysis. Computer digitization of an analog EEG signal is discussed, along with EEG filtering and the parameters o...

Introduction: Stress is a main factor influencing brain functions as revealed by the electroencephalogram (EEG) recordings. Moreover, different stress durations seemingly cause perturbations in brain waves and lead to mental disorders. This study investigates the effects of acute, sub-chronic and chronic stress on EEG in rats.  Methods: Twenty-eight Wistar adult male rats were randomly all...

Estimation of human emotions from Electroencephalogram (EEG) signals plays a vital role in developing robust Brain-Computer Interface (BCI) systems. In our research, we used Deep Neural Network (DNN) to address EEG-based emotion recognition. This was motivated by the recent advances in accuracy and efficiency from applying deep learning techniques in pattern recognition and classification appli...

UNLABELLED We studied the effects of intracerebroventricular injection of the novel neuropeptide orexin A on electroencephalogram (EEG) and autonomic nervous system activity in rats under isoflurane anesthesia. The administration of orexin A changed burst suppression patterns to arousal patterns on the EEG at 1.0 minimum alveolar anesthetic concentration (MAC) isoflurane and decreased the burst...

UNLABELLED We used quantitative topographical electroencephalography (EEG) to determine the time course of changes in brain electrical activity after clonidine infusion. Twenty healthy male volunteers (aged 24 +/- 5 yr) were included in the randomized, double-blind, placebo-controlled (Group 1, placebo, n = 10; Group 2, 2.0 micrograms/kg clonidine, n = 10) study. EEG (17 electrodes, common aver...