The development of automatic emotion detection systems has recently gained significant attention due to the growing possibility of their implementation in several applications, including affective computing and various fields within biomedical engineering. Use of the electroencephalograph (EEG) signal is preferred over facial expression, as people cannot control the EEG signal generated by thei...

Investigating human brain function non-invasively by simultaneous EEG and fMRI measurements is gaining in popularity as more and better solutions to the inherent technical challenges emerge. We demonstrate the use of a commercially available frequency divider and phase-locking device for the purpose of synchronizing an MRI acquisition with a simultaneous recording of the EEG. Synchronization hu...

The electroencephalogram (EEG) is an invaluable measurement for the purpose of assessing brain activities. The detection of epileptic seizures based on EEG signal is very useful in diagnostics. In this paper, we present a new method for discrimination between seizure and seizure-free EEG signals. The proposed method is based on empirical mode decomposition (EMD) process. We investigated that th...

Brain-computer interface (BCI) is a system to translate humans thoughts into commands. For electroencephalography (EEG) based BCI, motor imagery is considered as one of the most effective ways. This paper presents a method for classifying EEG during motor-imagery by the combination of well-known common spatial pattern (CSP) with so-called multivariate empirical mode decomposition (MEMD), which ...

Parallel to the breakthroughs on the usage of simultaneous EEG-fMRI in neurocognitive studies and research, the occurrence of artefacts in the EEG signal induced within the fMRI scanner constitutes one of the challenges to be overcome in order to broaden the range of applications of such a technique. It is the case of the gradient artefact, provoked by the variation of gradient magnetic fields....

Brain-computer interface (BCI) technology is a means of communication that allows individuals with severe movement disability to communicate with external assistive devices using the electroencephalogram (EEG) or other brain signals. This paper presents an alternative neural information processing architecture using Schrödinger wave equation for enhancement of the raw EEG signal. The raw EEG si...

Although the focus of attention on data degradation during simultaneous MRI/EEG recording has to date largely been upon EEG artefacts, the presence of the conducting wires and electrodes of the EEG recording system also causes some degradation of MRI data quality. This may result from magnetic susceptibility effects which lead to signal drop-out and image distortion, as well as the perturbation...

The electroencephalogram (EEG) is the most common tool used in sleep research. This unit describes the methods for recording and analyzing the EEG. Detailed protocols describe recorder calibration, electrode application, EEG recording, and computer EEG analysis with power spectral analysis. Computer digitization of an analog EEG signal is discussed, along with EEG filtering and the parameters o...

In the last couple of years, the EEG signal analysis was focused on epilepsy seizure detection. Epilepsy is a common chronic neurological disorder; they are result of transient and unexpected electrical disturbance of the brain. Epilepsy seizures also a symptom of brain tumor existence, 30% patients with brain tumor are affected with epilepsy seizure. This paper proposes a two level brain tumor...

electro encephalography is one of the reliable sources to detect sleep onset while driving. in this study we have tried to demonstrate that sleepiness and alertness signals are separable with an appropriate margin by extracting suitable features. so first of all we have recorded eeg signals from 10 volunteers. they were obliged to be sleep deprived about 20 hours before the test. we recorded th...