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In this paper we provide a quantitative electroencephalogram (EEG) analysis to study the effect of hypothermia on the neurological recovery of brain after cardiac arrest. We hypothesize that the brain injury results in a reduction in information of the brain rhythm. To measure the information content of the EEG a new measure called information quantity (IQ), which is the Shannon entropy of decorrelated...
A novel method is proposed here to determine whether a time series is deterministic even in the presence of noise. The method is the extension of an existing method based on smoothness analysis of the signal in state space with surrogate data testing. While classical measures fail to detect determinism when the time series is corrupted by noise, the proposed method can clearly distinguish between...
Driver sleepiness due to sleep deprivation is a causative factor in 1% to 3% of all motor vehicle crashes. In recent studies, the importance of developing driver fatigue countermeasure devices has been stressed, in order to help prevent driving accidents and errors. Although numerous physiological indicators are available to describe an individual's level of alertness, the EEG signal has been shown...
Progressive preictal dynamical convergence and postictal divergence of dynamical EEG descriptors among brain regions has been reported in human temporal lobe epilepsy (TLE) and in a rodent model of TLE. There are also reports of anticonvulsant effects of high frequency stimulation of the hippocampus in humans. We postulate that this anticonvulsant effect is due to dynamical resetting by the electrical...
The auditory steady-state responses (ASSR) elicited by click stimuli can be utilized for hearing screening as is traditionally done with click-evoked auditory brainstem responses (ABR). In a typical ASSR or ABR hearing screening, several recordings at different intensities are required to find the response threshold. In this study the use of binaural click stimulus with time ramping intensity produces...
Auditory evoked potentials (AEPs) have been recorded at high stimulus rates during sleep using continuous loop averaging deconvolution (CLAD) sequences. AEP transient signals are obtained via frequency domain deconvolution of overlapped responses. Simultaneous acquisition of auditory brainstem response (ABR), middle latency response (MLR), and long latency response (LLR) is obtained at an average...
Localization of the cognitive activity in the brain is one of the major problems in neuroscience. Current techniques for neuro-imaging are based on functional magnetic resonance imaging (fMRI), positron emission tomography (PET), and event related potential (ERP) recordings. The highest temporal resolution is achieved by ERP, which is crucial for temporal localization of activities. However, the spatial...
Conventional analysis of EEG signals for sleep scoring is based on the time domain assessment of wave patterns. Human experts carry out this task relying on the direct visualization of EEG epochs. Techniques that enhance an intuitive visualization may encourage a wider use of more abstract descriptors, such as frequency domain features. This paper presents a feature extraction method for EEG signals...
Despite much progress and research, fully reliable computer based epileptic seizure detection in EEG recordings is still elusive. This paper outlines a new strategy toward seizure detection. It is proposed that it is not the precise nature of a statistic that is important, but rather its variance over time. Using this, algorithms are presented that are able to successfully identify 97.6% of seizures...
In machine learning based Brain Computer Interfaces (BCIs), it is a challenge to use only a small amount of labelled data to build a classifier for a specific subject. This challenge was specifically addressed in BCI Competition 2005. Moreover, an effective BCI system should be adaptive to tackle the dynamic variations in brain signal. One of the solutions is to have its parameters adjustable while...
We introduce an adaptive space time frequency analysis to extract and classify subject specific brain oscillations induced by motor imagery in a brain computer interface task. The introduced method requires no prior knowledge of the reactive frequency bands, their temporal behavior or cortical locations. The algorithm implements an arbitrary time-frequency segmentation procedure by using a flexible...
High frequency oscillations (HFO) in limbic epilepsy represent a marked difference between abnormal and normal brain activity. Faced with the difficult of visually detecting HFOs in large amounts of intracranial EEG data, it is necessary to develop an automated process. This paper presents Teager Energy as a method of finding HFOs. Teager energy is an ideal measure because unlike conventional energy...
Deception detection has important clinical and legal implications. However, the reliability of methods for the discrimination between truthful and deceptive responses is still limited. Efforts to improve reliability have examined measures of central nervous system function such as EEG. However, EEG analyses based on either time- or frequency-domain parameters have had mixed results. Because EEG is...
The dynamic profile of multi parameters of electroencephalogram (EEG) pathology associated with middle cerebral ischemia occlusion in a rat model were measured. Both pronounced increase in delta activity and decrease in theta activity during ischemic injuries were observed accompanied with decrease in the complexity of EEG. Different characteristic dynamic profiles might imply different mechanism...
Binocular rivalry is a visual perceptual phenomenon which occurs when two incongruent stimuli are viewed by a subject through each eye, but only one of them is perceived at a time, with a switch in perception every few seconds, which reflects the alternation of perceptual dominance. To investigate the correlation between contrast-related perception and neural activities, the subjects' EEGs were recorded...
EEG forward problem solution using numerical head models with the same resolution and geometry as that available from MRI is desirable. This implies dealing with realistic head models of over 2 million elements, for which problem solution has so far been impractical due to issues of computation time and memory. This paper investigates the possibilities given by high performance computing (HPC) to...
We present a forward problem formulation for computing biopotentials measured with dry or capacitive electrodes. This formulation is not quasistatic and has mixed boundary conditions. Our results show that simple approximations to the measurements based on capacitive coupling are adequate in most situations. We study the range of validity and errors committed in the EEG forward and inverse problems...
Accurate head modeling is required to properly simulate bioelectric phenomena in 3-D as well as to estimate the 3-D bioelectric activity starting from superficial bioelectric measurements and 3-D imaging. Aiming to build an accurate and realistic representation of the volume conductor of the head, also the anisotropy of head tissues should be taken into account. In this paper we describe a new finite-difference...
In order to analyse non-stationary signals, like neonatal EEG, it is sometimes easier to segment signals into pseudo-stationary segments. An evaluation was performed on three previously proposed EEG segmentation methods in order to determine which method is most suited to neonatal EEG analysis. The three methods evaluated are spectral error measurement (SEM), generalised likelihood ratio (GLR) and...
Artifact removal is an essential part in electroencephalogram (EEG) recording and the raw EEG signals require preprocessing before feature extraction. In this work, we implemented three filtering methods and demonstrated their effects on the performance of different classifiers. Bandpass digital filtering, median filtering and facet method are three preprocessing approaches investigated in this paper...
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