More importantly, theta band SL on the first EEG proved to be a significant predictor of the diagnosis 'epilepsy'epilepsy
Synchronization between the SR-BIS and SR-EEG data proved to be a challenge.
Electroencephalograms (EEGs) have proven to be a useful tool for monitoring the brain activity of adults undergoing anesthesia, but studies have found EEG-based monitoring to be unreliable in infants under anesthesia.
The paper is based on the fact that features extracted from electroencephalogram (EEG) recordings have proved to be unique enough across subjects for biometric applications.
EEG has been proven to be a kind of nonlinear, nonstationary, and chaotic time series [ 5], providing information about spatiotemporal patterns of brain electrical activity [ 6].
In several studies spectral analysis of EEG has been proven to be a valuable, sensitive and observer –independent method to detect minimal HE [ 19, 26], therefore it can be used as a reference tool and we applied it in our study as well.
The quantitative evaluation using simulated EEGs with outliers proves that the proposed Lp (p ≤ 1) AR can estimate the AR parameters more robustly than the Yule Walker, Burg and LS methods, under various simulated outlier conditions.
Besides the clinical avenues such as neuropsychological inventories, further investigations with a longitudinal design proving lasting Ecstasy effects on EEG in polydrug users are of special interest and may be beneficial for the ongoing discussion of the neurotoxicity particularly of common substances of Ecstasy in humans [36].
Furthermore, coil positioning using the 10 20 EEG-system has been proven to guarantee exact placement of the TMS coil over the auditory cortex without the need of using MR- and PET-guidance.
Cloostermans et al. [ 27] proved that continuous EEG patterns within 12 hrs predicted good outcome while an isoelectric or low-voltage electroencephalograms after 24 hrs predicted poor outcome in patients treated with hypothermia.
The singular values and vectors have proved useful in characterizing EEG abnormalities [13, 74].
