In Electroencephalography (EEG) processing one of the crucial step is to select the features which can be used to characterize the different patterns. This paper presents relative wavelet energy as a new feature extraction technique to recognize the sleep EEG patterns. Experimental results on the Physionet databases with different sleep stages indicate that the relative wavelet energy is a comp...

OBJECTIVE The purpose of the study was to evaluate quantitative sleep electroencephalogram (EEG) frequencies in monozygotic twins discordant for chronic fatigue syndrome. METHODS Thirteen pairs of female twins underwent polysomnography. During the first night, they adapted to the sleep laboratory, and during the second night, their baseline sleep was assessed. Visual stage scoring was conduct...

Sleeping brain activity reflects brain anatomy and physiology. The aim of this study was to use high density (256 channel) electroencephalography (EEG) during sleep to characterize topographic changes in sleep EEG power across normal aging, with high spatial resolution. Sleep was evaluated in 92 healthy adults aged 18-65 years old using full polysomnography and high density EEG. After artifact ...

Sepsis is a systemic immune response to infection that may result in multiple organ failure and death. Polymicrobial infections remain a serious clinical problem, and in the hospital sepsis is the number one non-cardiac killer. Although the central nervous system may be one of the first systems affected, relatively little effort has been made to determine the impact of sepsis on the brain. In t...

This study was concentrated on changes of complexity of EEG signals during the sleep onset process and the comparison of sleep onset with relaxation. The ability of two complexity measures correlation dimension D2 and fractal exponent γ to distinguish these slightly distinct states was examined. Both measures confirmed decreased complexity of EEG signals during sleep onset process, on the contr...

Automatic classification of sleep stages is one of the most important methods used for diagnostic procedures in psychiatry and neurology. This method, which has been developed by sleep specialists, is a time-consuming and difficult process. Generally, electroencephalogram (EEG) signals are used in sleep scoring. In this study, a new complex classifier-based approach is presented for automatic s...

Studies of ionotropic receptors indicate that glutamate (Glu) neurotransmission plays a role in sleep. Here, we show for the first time that metabotropic 2/3 Glu (mGlu2/3) receptors play an active or permissive role in the control of REM sleep. The potent, selective, and systemically active mGlu2/3 receptor agonist LY379268 was administered systemically in doses of 1.0 and 0.25 mg/kg sc. The dr...

Sleep spindles are bursts of rhythmic activity characterized by progressively increasing, then gradually decreasing amplitude, present predominantly in stages 2, 3 and 4 of the sleep electroencephalogram (EEG). Topographic analyses of sleep spindle incidence suggested the existence of two distinct sleep spindle types, “slow” and “fast” spindles at approximately 12 and 14 Hz respectively. There ...

BACKGROUND This paper addresses the problem of detecting sleep spindles and K-complexes in human sleep EEG. Sleep spindles and K-complexes aid in classifying stage 2 NREM human sleep. NEW METHOD We propose a non-linear model for the EEG, consisting of a transient, low-frequency, and an oscillatory component. The transient component captures the non-oscillatory transients in the EEG. The oscil...

BACKGROUND In addition to the cost and complexity of processing multiple signal channels, manual sleep staging is also tedious, time consuming, and error-prone. The aim of this paper is to propose an automatic slow wave sleep (SWS) detection method that uses only one channel of the electroencephalography (EEG) signal. NEW METHOD The proposed approach distinguishes itself from previous automat...