A communication path for people having severe neural disorders is provided by Brain Computer Interaction. The Brain–Computer Interface in an electroencephalogram important and challenging one managing non-stationary EEG signals. signals are more vulnerable to noise artifacts. Motor Imagery-based used as a channel with who have no muscular activity. For well-established accurate BCI system, two ...

During the sleep-wake cycle, brain undergoes profound dynamical changes, which manifest subjectively as transitions between conscious experience and unconsciousness. Yet, neurophysiological signatures that can objectively distinguish different consciousness states based are scarce. Here, we show differences in level of brain-wide signals reliably stages sleep anesthesia from awake state human m...

within the neuroscience and computational neuroscience communities, applications such as evaluating different cognitive responses of the brain, brain-computer interface (bci) systems and brain connectivity studies have increasingly been using eeg phase information during the past few decades. the utility of eeg phase can be directly linked to the neural propagation and synchronized firing of ne...

Brain-Computer interface systems are a new mode of communication which provides a new path between brain and its surrounding by processing EEG signals measured in different mental states.  Therefore, choosing suitable features is demanded for a good BCI communication. In this regard, one of the points to be considered is feature vector dimensionality. We present a method of feature reduction us...

Emotion awareness is one of the most important subjects in field affective computing. Using nonverbal behavioral methods such as recognition facial expression, verbal method, speech emotion, or physiological signals-based emotions based on electroencephalogram (EEG) can predict human emotion. However, it notable that data obtained from either behaviors are indirect emotional signals suggesting ...

This study aims at investigation of stimulation by using intra-spinal signals decoded from electrocorticography (ECoG) assessments to restore the movements of the leg in an animal model of spinal cord injury (SCI). The present work comprised of three steps. First, ECoG signals and the associated leg joint changes (hip, knee, and ankle) in sedated healthy rabbits were recorded in different trial...

Mohamed Elgendi1,2, Brice Rebsamen3, Andrzej Cichocki4, Francois Vialatte4,5, Justin Dauwels2 1Institute for Media Innovation, Nanyang Technological University, Singapore, 2School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, 3Temasek Laboratories, National University of Singapore, Singapore, 4Lab. ABSP, RIKEN Brain Science Institute, Wako-Shi, Japan, 5E...

background: epilepsy is a severe disorder of the central nervous system that predisposes  the person to recurrent seizures. fifty million people worldwide suffer from  epilepsy; after alzheimer's and stroke, it is the third widespread nervous disorder. objective: in this paper, an algorithm to detect the onset of epileptic seizures  based on the analysis of brain electrical signals (eeg) has be...