The paper deals with the presence of exponential or power-law decay in the power spectra of electroencephalogram (EEG). About 2300 EEG time series recorded during relaxed wakefulness were analysed. The whole spectrum of EEG was studied and power-law decay of about 2.28 prevailing over the exponential falling off was established. Correspondence between spectrum power-law decay and correlation di...

The objective of our study was to examine the electroencephalogram (EEG) abnormalities associated with clozapine treatment. It was a cross-sectional study on 87 psychiatric patients on clozapine treatment. 32 channel digital EEG was recorded and analysed visually for abnormalities. EEG abnormalities were observed in 63.2% of patients. Both slowing and epileptiform activities were noted in 41.4%...

Motor imagery as rehabilitation method after stroke is becoming an important tool and is currently also heavily researched. One issue, however, is to quantify and monitor changes in the ongoing brain activity and to document brain plasticity. Here, we analyze the electroencephalogram (EEG) of hemiparetic stroke patients during left hand and right hand motor imagery in order to determine whether...

Two cases, both children, are described, in which there was a return of the electroencephalogram after a period of electrocerebral silence. One child survived for six weeks. Electroencephalographic technique and instrumentation adequately excluded non-cerebral potentials as a source of confusion in the second case. Hypothermia and drug overdosage, known to reversibly depress the electroencephal...

The electroencephalogram (EEG) is a complex signal and an important brain state indicator (e.g. waking, sleep, seizure). Modern brain research is intimately linked to the feasibility to record the EEG and to its quantitative analysis. EEG spectral analysis (decomposing a signal into its constituent frequency components) is an important method to investigate brain activity. Basic principals of s...

This letter reports on the effectiveness of applying K-singular value decomposition (SVD) dictionary learning to electroencephalogram (EEG) compressed sensing framework with outlier detection and independent component analysis. Using K-SVD matrix our design parameter optimization, for example, at compression ratio four, we improved normalized mean square error by 31.4% compared that discrete co...

The Electroencephalogram (EEG) is a biological signal that represents the electrical activity of the brain. Artifacts in EEG signals are caused by various factors, like line interference, EOG (electro-oculogram) and ECG (electrocardiogram). The removal of artifact from scalp EEGs is of considerable importance for analysis of underlying brainwave activity. The presence of artifacts such as muscl...

In the paper, we use Microsoft’s Visual Studio Development Kit and the C# programming language to implement chaos-based electroencephalogram (EEG) encryption system with three encryption levels. A chaos logic map, an initial value, and a bifurcation parameter for the map are used to generate level I chaosbased EEG encryption bit streams. Two encryption-level parameters are added to these elemen...