The fields of presence research and electroencephalography (EEG) are related in, at least, two ways. Firstly, EEG can be used to analyse the neurophysiological phenomena related to presence research. For example, EEG might be useful to investigate the question of ‘breaks in presence’. Secondly, EEG can be used to control external devices with a so-called “brain computer interface” (BCI). Such a...

Copyright: © 2013 Graan LAV, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Abbreviations: AED: Antiepileptic Drugs; BOLD: Blood Oxygen Level Dependent; DMN: Default Mode Network; ECG: Electrocardiogra...

This paper describes undergraduate electroencephalography projects using the OpenEEG platform. The projects applied a broad range of curriculum components including computer interfacing, signal processing and software development. Project applications were wide-ranging and provided opportunities to explore research areas such as Brain-Computer Interfacing , affective computing and assistive tec...

Introduction The purpose of this study was to characterize resting-state cortical networks in chronic stroke survivors using electroencephalography (EEG). Methods Electroencephalography data were collected from 14 and 11 neurologically intact participants while they a relaxed, resting state. EEG power normalized reduce bias used as an indicator network activity. Correlations orthogonalized acti...

BACKGROUND Poor agreement between observers on whether an unusual event is a seizure drives the need for a specific diagnostic tool provided by video-electroencephalography (video-EEG) in human pediatric epileptology. OBJECTIVE That successful classification of events would be positively associated with increasing EEG recording length and higher event frequency reported before video-EEG evalu...

It is incredibly challenging to build an intelligent algorithm for emotion recognition that can deliver high accuracy because electroencephalography (EEG) signals are not stationary, nonlinear, and noisy. First, decomposing the preprocessed EEG of SEED dataset into five frequency bands: delta, theta, alpha, beta, gamma, then calculated their energy entropy from extracted features. Then Principa...

Video EEG monitoring (VEM) is a valuable tool for the diagnosis of epileptic seizures (ES) and psychogenic nonepileptic seizures (PNES). We sought to determine the benefits of prolonged length of stay (LOS). We retrospectively reviewed the records of patients admitted for VEM. We analyzed LOS for ES and PNES patients to determine if there was reduced utility, as evidenced by a significantly hig...

© The Author(s) 2014 C. Guger et al. (eds.), Brain-Computer Interface Research, SpringerBriefs in Electrical and Computer Engineering, DOI 10.1007/978-3-319-09979-8_6 Abstract We present a radically new way of recording EEG comfortably and unobtrusively over long time-periods in natural environments. This break-through has been achieved using electrodes embedded on a customized earpiece as typi...