Research on electroencephalogram (EEG) characteristics associated with major depressive disorder (MDD) has accumulated diverse neurophysiologic findings related to the content, topography, neurochemistry, and functions of EEG oscillations. Significant progress has been made since the first landmark EEG study on affective disorders by Davidson 35 years ago. A systematic account of these data is ...

Abstract Practical sensing of biopotentials such as the electroencephalogram (EEG) in operational settings has been severely limited by the need for skin preparation and conductive electrolytes at the skin-sensor interface. Another seldom-noted problem has been the need for a low impedance connection from the body to ground for cancellation of common-mode noise voltages. In this article we desc...

The paper relates to possible connection between spectrum power-law decay and correlation dimension estimation for electroencephalogram (EEG). EEG signals recorded during relaxed wakefulness were analysed. Power-law decay of about 2.28 prevailing over the exponential falling off was established when exponent from the whole EEG spectrum was taken. The correlation dimension was also estimated. Th...

Balance design taking game difficulty into account has an important role in game design. In recent years, a number of studies have tried to adjust difficulty by using various player dependent difficulty detection algorithms. But most of these methods need customizing its algorithm for each game. In this paper, we investigate the way to find adaptive game difficulty levels according to player’s ...

We further explore the possibility of using the energy of brain potentials evoked during processing of visual stimuli (VS) as a new biometric tool, where biometric features representing the energy of high frequency electroencephalogram (EEG) spectra are used in the person identification paradigm. For convenience and ease of processing of cognitive processing, in the experiments, simple black an...

PURPOSE The purpose of this case report is to document a patient with cinematographic hallucinations, with corresponding right temporal lobe seizures on electroencephalogram (EEG). RESULTS The results showed that the patient's EEG was normal. The patient subsequently reported hallucinations, which had been occurring for the last several months. During monitoring, no interictal EEG abnormaliti...

Classifying different electroencephalogram (EEG) patterns is one of the key components to designing a usable Brain Computer Interface (BCI). Although it is well known that Support Vector Machine (SVM) is a strong classifier, it does not replace simple Linear Discriminant Analysis (LDA) or Nearest Neighbor Classifier (NNC), which are still in use in current BCI systems. This paper presents a com...

Brain responses to audio stimuli are analysed using data driven time-frequency analysis. This is achieved based on the electroencephalogram (EEG) recordings and with auditory chirps or music as the audio stimulus. The empirical mode decomposition (EMD) is applied to multichannel EEG recordings, and the insight into the brain responses is provided by the analysis of the dynamics of auditory stea...

Traditional brain-computer interface (BCI) research has forked to consider not only disabled patients but able-bodied users as well. Among various biosignals, electroencephalogram (EEG) is a cheap, portable and popular means of accessing brain activity. As a result, EEG-based BCIs are gradually being used in everyday applications, including games. Just as any computer product, human-computer in...

Electroencephalogram (EEG) reflects the brain activity and is widely used in biomedical research. However, analysis of this signal is still a challenging issue. This paper presents a hybrid approach for assessing stress using the EEG signal. It applies Multivariate Multi-scale Entropy Analysis (MMSE) for the data level fusion. Case-based reasoning is used for the classification tasks. Our preli...