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BACKGROUND Sleep staging is a critical step in a range of electrophysiological signal processing pipelines used in clinical routine as well as in sleep research. Although the results currently achievable with automatic sleep staging methods are promising, there is need for improvement, especially given the time-consuming and tedious nature of visual sleep(More)
Recent studies have reported that discrete high frequency oscillations (HFOs) in the range of 80-500Hz may serve as promising biomarkers of the seizure focus in humans. Visual scoring of HFOs is tiring, time consuming, highly subjective and requires a great deal of mental concentration. Due to the recent explosion of HFOs research, development of a robust(More)
Keywords: Epilepsy High-frequency oscillations (HFOs) Intracereberal EEG Empirical mode decomposition (EMD) Hilbert spectral analysis (HSA) Root mean square (RMS) a b s t r a c t Discrete high-frequency oscillations (HFOs) in the range of 80–500 Hz have previously been recorded from human epileptic brains using intracereberal EEG and seem to be a reliable(More)
Visuospatial attention can be deployed to different locations in space independently of ocular fixation, and studies have shown that event-related potential (ERP) components can effectively index whether such covert visuospatial attention is deployed to the left or right visual field. However, it is not clear whether we may obtain a more precise spatial(More)
A novel framework for joint detection of sleep spindles and K-complex events, two hallmarks of sleep stage S2, is proposed. Sleep electroencephalography (EEG) signals are split into oscillatory (spindles) and transient (K-complex) components. This decomposition is conveniently achieved by applying morphological component analysis (MCA) to a sparse(More)
Spikes and sharp waves recorded on scalp EEG may play an important role in identifying the epileptogenic network as well as in understanding the central nervous system. Therefore, several automatic and semi-automatic methods have been implemented to detect these two neural transients. A consistent gold standard associated with a high degree of agreement(More)
Epilepsy is one of the most common neurological disorders and affects almost 60 million people worldwide; many techniques were used to detect epileptic activities in the EEG recording. In this study we have used detection method based on linear prediction error. The main idea of this method is that LP filter can not track sudden changes caused by spikes and(More)
Epilepsy is one of the most common neurological disorders and affects almost 60 million people worldwide; many techniques were used to detect epileptic seizures in the EEG recording. In this study we have implemented the new non linear epileptic seizure detection, proposed by H.Ocak, the method is based on discrete wavelet analyse and Approximate Entropy.(More)
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