The aim of the study was to design, develop and evaluate a general-purpose EEG platform which integrates with smartphone. target specification system 19 channels data stored onto smartphone via Wi-Fi connection. hardware developed using three ADS1299 integrated circuits, game engine, Unity, used app. An evaluation conducted recordings alpha waves during periods eye closure in participants (Blan...

We describe a spatio-temporal linear discriminator for single-trial classification of multi-channel electroencephalography (EEG). No prior information about the characteristics of the neural activity is required, i.e., the algorithm requires no knowledge about the timing and spatial distribution of the evoked responses. The algorithm finds a temporal delay/window onset time for each EEG channel...

Obtaining a quality EEG in the intensive care unit (ICU) is a very rewarding experience for the EEG technologist. "Quality" is defined as a measure of excellence or state of being free from defects. It takes more than knowing how to obtain a quality record; it takes hands-on experience and time. Electroencephalography is a valuable neurodiagnostic tool in critically ill patients. However, the I...

Directed connectivity between brain sources identified from scalp electroencephalography (EEG) can shed light on the brain’s information flows and provide a biomarker of neurological disorders. However, as volume conductance results in activity being mix activities originating multiple sources, correct interpretation their is formidable challenge despite source localization applied with some su...

We describe a phantom for simultaneous electroencephalography (EEG) and near-infrared imaging which consists of a solid, optically turbid and electrically conducting interface enclosing a tissue-mimicking aqueous scattering solution. The interface provides an electrical contact impedance comparable to that of the human scalp while the phantom as a whole has optical properties and electrical con...

In this article, signal-to-noise ratio (SNR) criterion is investigated with the object of determining the level of its ability to distinguish between Event Related Potentials (ERPs) and noise signals in ElectroEncephaloGraphy (EEG) data. For this purpose a new algorithm (SNRMAX) based on SNR maximization and intended for extracting a linear subspace related to ERPs from EEG data is developed. T...

Characterizing functional brain networks in humans during magnetophosphene perception. Dense electroencephalography (EEG, 128 channels) was performed in N=3 volunteers during high-level (50 mT) magnetic field (MF) exposure. Functional brain networks were reconstructed, at the cortical level from scalp recordings, using the EEG source connectivity method. Magnetophosphene perception appears to c...

Electroencephalography (EEG) based preliminary examination system has been proposed in the clinical brain death determination. This paper presents a novel data analysis algorithm based on multivariate empirical mode decomposition (MEMD) to calculate and evaluate the energy of EEG recorded from the comatose patients and brain deaths. MEMD is an extended approach of empirical mode decomposition (...