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Physical principles of brain–computer interfaces and their applications for rehabilitation, robotics and control of human brain states
Brain–computer interfaces (BCIs) development is closely related to physics. In this paper, we
review the physical principles of BCIs, and underlying novel approaches for registration …
review the physical principles of BCIs, and underlying novel approaches for registration …
A tutorial for information theory in neuroscience
Understanding how neural systems integrate, encode, and compute information is central to
understanding brain function. Frequently, data from neuroscience experiments are …
understanding brain function. Frequently, data from neuroscience experiments are …
A multivariate approach for patient-specific EEG seizure detection using empirical wavelet transform
Objective: This paper investigates the multivariate oscillatory nature of
electroencephalogram (EEG) signals in adaptive frequency scales for epileptic seizure …
electroencephalogram (EEG) signals in adaptive frequency scales for epileptic seizure …
Visual and kinesthetic modes affect motor imagery classification in untrained subjects
The understanding of neurophysiological mechanisms responsible for motor imagery (MI) is
essential for the development of brain-computer interfaces (BCI) and bioprosthetics. Our …
essential for the development of brain-computer interfaces (BCI) and bioprosthetics. Our …
Extreme value theory inspires explainable machine learning approach for seizure detection
Epilepsy is one of the brightest manifestations of extreme behavior in living systems.
Extreme epileptic events are seizures, that arise suddenly and unpredictably. Usually …
Extreme epileptic events are seizures, that arise suddenly and unpredictably. Usually …
Artificial Neural Network Classification of Motor‐Related EEG: An Increase in Classification Accuracy by Reducing Signal Complexity
We apply artificial neural network (ANN) for recognition and classification of
electroencephalographic (EEG) patterns associated with motor imagery in untrained …
electroencephalographic (EEG) patterns associated with motor imagery in untrained …
Statistical properties and predictability of extreme epileptic events
The use of extreme events theory for the analysis of spontaneous epileptic brain activity is a
relevant multidisciplinary problem. It allows deeper understanding of pathological brain …
relevant multidisciplinary problem. It allows deeper understanding of pathological brain …
Absence seizure control by a brain computer interface
The ultimate goal of epileptology is the complete abolishment of epileptic seizures. This
might be achieved by a system that predicts seizure onset combined with a system that …
might be achieved by a system that predicts seizure onset combined with a system that …
Open-loop neuroadaptive system for enhancing student's cognitive abilities in learning
Neuroeducation seeks to implement knowledge about neural mechanisms of learning into
educational practice and to understand the impact of learning itself. The crucial tasks in this …
educational practice and to understand the impact of learning itself. The crucial tasks in this …
Functional networks of the brain: from connectivity restoration to dynamic integration
A review of physical and mathematical methods for reconstructing the functional networks of
the brain based on recorded brain activity is presented. Various methods are considered, as …
the brain based on recorded brain activity is presented. Various methods are considered, as …