Electroencephalography (EEG), which contains cortical potentials during various mental processes, can be used to provide neural input signals to activate a brain machine interface (BMI). The effectiveness of such an EEG-based prosthetic system would rely on correct classification of executed motor signals from imagined motor movement signals; an executed motor signal should initiate movement in...

Brain Computer Interface (BCI) can help patients of neuromuscular diseases restore parts of the movement and communication abilities that they have lost. Most of BCIs rely on mapping brain activities to device instructions, but limited number of brain activities decides the limited abilities of BCIs. To deal with the problem of limited ablility of BCI, this paper verified the feasibility of con...

Brain Electroencephalography (EEG) classification is widely applied to analyze cerebral diseases in recent years. Unfortunately, invalid/noisy EEGs degrade the diagnosis performance and most previously developed methods ignore the necessity of EEG selection for classification. To this end, this paper proposes a novel maximum weight clique-based EEG selection approach, named mwcEEGs, to map EEG ...

Electroencephalography is a technique for recording the brain’s electrical activity – the electroencephalogram or EEG. It is an important procedure in the diagnosis of several brain disorders, as well being a valuable physiological tool for studies of normal brain function. However, the EEG is often contaminated by numerous artefacts such as eye-blinks, muscle activities, and eye-movements. Thi...

Some studies have reported the importance of electroencephalography (EEG) as a method for investigating abnormal parameters in psychiatric disorders. Different findings in time and frequency domain analysis with regard to central nervous system arousal during acute panic states have already been obtained. This study aimed to systematically review the EEG findings in panic disorder (PD), discuss...

OBJECTIVE To investigate the effect of force level and fatigue on brain activity during handgrip tasks. METHODS Electroencephalography (EEG) signals were recorded from eleven healthy male subjects when they performed 25%, 50% and 75% maximal voluntary contraction (MVC), and were in fatigue state. EEG powers in different handgrip tasks were analyzed in the frequency domain and time domain resp...

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) provide complementary noninvasive information of brain activity, and EEG/fMRI fusion can achieve higher spatiotemporal resolution than each modality separately. This focuses on independent component analysis (ICA)-based EEG/fMRI fusion. In order to appreciate the issues, we first describe the potential an...

Since ischemic stroke is an extremely common and dangerous pathology, it important to use drugs with neuroprotective activity. The depth degree of brain damage due ischemia are reflected in its bioelectrical This makes possible the electrocorticography or intracranial electroencephalography (EEG) as a tool for evaluating effectiveness therapy. In present study properties experimental compound R...

<p>In this paper, the English speaking proficiency level of non-native speakers<br />was automatically estimated as high, medium, or low performance. For purpose, speech 142 speakers was recorded and electroencephalography (EEG) signals 58 them were while in English. Two systems proposed for estimating speaker; one used 72 audio features, extracted from signals, other 112 features E...

The driver's cognitive and physiological states affect his/her ability to control the vehicle. Thus, these driver are essential safety of automobiles. design advanced assistance systems (ADAS) or autonomous vehicles will depend on their interact effectively with driver. A deeper understanding state is, therefore, paramount. Electroencephalography (EEG) is proven be one most effective methods fo...