The study of electroencephalography (EEG) signals is not a new topic. However, the analysis of human emotions upon exposure to music considered as important direction. Although distributed in various academic databases, research on this concept is li...
Assistive technologies help all persons with disabilities to improve their accessibility in all aspects of their life. The AIDE European project contributes to the improvement of current assistive technologies by developing and testing a modular and ...
Visual scene category representations emerge very rapidly, yet the computational transformations that enable such invariant categorizations remain elusive. Deep convolutional neural networks (CNNs) perform visual categorization at near human-level ac...
Computational and mathematical methods in medicine
Jul 22, 2018
A neuromuscular interface (NI) that can be employed to operate external robotic devices (RD), including commercial ones, was proposed. Multichannel electromyographic (EMG) signal is used in the control loop. Control signal can also be supplemented wi...
The categorization of food via sensing nutrients or toxins is crucial to the survival of any organism. On ingestion, rapid responses within the gustatory system are required to identify the oral stimulus to guide immediate behavior (swallowing or exp...
Journal of experimental psychology. Learning, memory, and cognition
Jul 19, 2018
Dual-process models of recognition memory typically assume that independent familiarity and recollection signals with distinct temporal profiles can each lead to recognition (enabling 2 routes to recognition), whereas single-process models posit a un...
Exploring brain networks is an essential step towards understanding functional organization of the brain, which needs characterization of linear and nonlinear connections based on measurements like EEG or MEG. Conventional measures of connectivity ar...
IEEE journal of biomedical and health informatics
Jul 17, 2018
Analyzing patients' health data using machine learning techniques can improve both patient outcomes and hospital operations. However, heterogeneous patient data (e.g., vital signs) and inefficient feature learning methods affect the implementation of...
PURPOSE: Quasi-stable electrical distribution in EEG called microstates could carry useful information on the dynamics of large scale brain networks. Using machine learning techniques we explored if abnormalities in microstates can identify patients ...
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Jul 9, 2018
OBJECTIVE: Visual assessment of the EEG still outperforms current computer algorithms in detecting epileptiform discharges. Deep learning is a promising novel approach, being able to learn from large datasets. Here, we show pilot results of detecting...
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