OBJECTIVE: Electroencephalography (EEG) motor imagery classification has been widely used in healthcare applications such as mobile assistive robots and post-stroke rehabilitation. Recently, EEG motor imagery classification methods based on convoluti...
OBJECTIVE: Somatic symptom disorder (SSD) is a reflection of medically unexplained physical symptoms that lead to distress and impairment in social and occupational functioning. SSD is phenomenologically diagnosed and its neurobiology remains unsolve...
OBJECTIVE: Translational studies on motor control and neurological disorders require detailed monitoring of sensorimotor components of natural limb movements in relevant animal models. However, available experimental tools do not provide a sufficient...
OBJECTIVE: Attention-deficit/hyperactivity disorder (ADHD) is one of the most prevalent neurobehavioral disorders. Studies have tried to find the neural correlations of ADHD with electroencephalography (EEG). Due to the heterogeneity in the ADHD popu...
OBJECTIVE: The aim of this study was to evaluate the effect of electroencephalographic (EEG) volume conduction in different measures of functional connectivity and to characterize the EEG coupling alterations at the different stages of dementia due t...
OBJECTIVE: Currently, the automatic sleep staging methods mainly face two problems: the first problem is that although the algorithms which use electroencephalogram (EEG) signals perform well, acquiring EEG signals is complicated and uncomfortable; t...
OBJECTIVE: Convolutional neural networks (CNNs) have proven successful as function approximators and have therefore been used for classification problems including electroencephalography (EEG) signal decoding for brain-computer interfaces (BCI). Arti...
OBJECTIVE: The identification of functional regions, in particular the subthalamic nucleus, through microelectrode recording (MER) is the key step in deep brain stimulation (DBS). To eliminate variability in a neurosurgeon's judgment, this study pres...
OBJECTIVE: Learning the structures and unknown correlations of a motor imagery electroencephalogram (MI-EEG) signal is important for its classification. It is also a major challenge to obtain good classification accuracy from the increased number of ...
OBJECTIVE: Robotic positioning systems for transcranial magnetic stimulation (TMS) promise improved accuracy and stability of coil placement, but there is limited data on their performance. Investigate the usability, accuracy, and limitations of robo...