Since electroencephalographic (EEG) signal may be considered chaotic, Nonlinear Dynamics and Deterministic Chaos Theory may supply effective quantitative descriptors of EEG dynamics and of underlying chaos in the brain. We have used Karhunen-Loeve decomposition of the covariance matrix of the EEG signal to analyse EEG signals of 4 healthy subjects, under drug-free condition and under the influe...

The Electroencephalogram (EEG) is a biological signal that represents the electrical activity of the brain. Eye-blinks and movement of the eyeballs produce electrical signals that are collectively known as Ocular Artifacts (OA). These are of the order of milli-volts and they contaminate the EEG signals which are of the order of micro-volts. The frequency range of EEG signal is 0 to 64 Hz and th...

This paper presents a novel approach for removing gradient artefacts from the EEG signal recorded during continuous EEG-fMRI, which are influenced by transient head movements of the subject within the magnetic scanner. Transient head movements provoke abrupt changes in the gradient artefact waveform, in such a way that they compromise the estimation of an artefact waveform to be subtracted and ...

wet ag/agcl electrodes, although very popular in clinical diagnosis, are not appropriate for expanding applications of wearable biopotential recording systems which are used repetitively and for a long time. here, the development of a low‑cost and low‑noise active dry electrode is presented. the performance of the new electrodes was assessed for recording electrocardiogram (ecg) and electroence...

In recent years, Brain-Computer Interface (BCI) system gained much popularity since it aims at establishing the communication between human brain and computer. BCI systems are applied in several research areas such as neuro-rehabilitation, robots, exoeskeletons, etc. Electroencephalography (EEG) is a technique commonly capturing signals. It incorporated has attractive features non-invasive natu...

Abstract Background Oscillations in the resting-state scalp electroencephalogram (EEG) represent various intrinsic brain activities. One of characteristic EEG oscillations is sensorimotor rhythm (SMR)—with its arch-shaped waveform alpha- and betabands—that reflect activity. The representation activity by SMR depends on signal-to-noise ratio achieved spatial filters. New method We employed simul...