This paper proposes a method for automatic detection of seizure onset. Two statistical features: skewness and kurtosis with a wavelet based feature: normalized coefficient of variation (NCOV) were extracted from the data. The classification between normal and seizure EEGs was performed using simple linear classifier. The performance of the algorithm was tested on the 10 patient’s data of CHB-MI...

BACKGROUND Genetic rat models for childhood absence epilepsy have become instrumental in developing theories on the origin of absence epilepsy, the evaluation of new and experimental treatments, as well as in developing new methods for automatic seizure detection, prediction, and/or interference of seizures. METHOD Various methods for automated off and on-line analyses of ECoG in rodent model...

Background: More than 80% of neonatal seizures are completely subclinical and represent a risk factor for neurodevelopmental delays in preterm infants. Amplitude integrated electroencephalography combined with raw video images (video aEEG/EEG) provides real-time monitoring seizure detection.

This paper considers a system design for processing a multidimensional biomedical signal formed by EEG, ECG, EOG and motion recorded from a newborn, for the purpose of detection of epileptic seizures in newborns as an extension of the method reported in [1, 8]. We describe the proposed design, and discuss how the signals will be analysed and fused to detect the occurrence of seizure. We also di...

The statistical properties of seizure EEG are found to be different from that of the normal EEG. This paper ascertains the efficacy of inter quartile range (IQR), a median based measure of statistical dispersion, as a discriminating feature that can be used for the classification of EEG signals into normal, interictal and ictal classes. IQR along with variance and entropy are calculated for eac...

This review surveys current seizure detection and classification technologies as they relate to aiding clinical decision-making during epilepsy treatment. Interviews and data collected from neurologists and a literature review highlighted a strong need for better distinguishing between patients exhibiting generalized and partial seizure types as well as achieving more accurate seizure counts. T...

In integrable many-particle systems, it is widely believed that the stationary state reached at late times after a quantum quench can be described by a generalized Gibbs ensemble (GGE) constructed from their extensive number of conserved charges. A crucial issue is then to identify a complete set of these charges, enabling the GGE to provide exact steady-state predictions. Here we solve this lo...

The dynamical characteristics of a complex system can be inferred from an observation of the system. In this paper, a calculation algorithm of the damping time of a signal from a complex system is presented by using information retrieve and autoregressive model. Two EEG recordings during tonic–clonic seizure are analyzed; the damping time of EEG calculated by means of the proposed algorithm can...

Ultra-low power operation and extreme energy efficiency are strong requirements for a number of high-growth application areas requiring near-sensor processing, including elaboration of biosignals. Parallel near-threshold computing is emerging as an approach to achieve significant improvements in energy efficiency while overcoming the performance degradation typical of low-voltage operations. In...