Physical principles of brain–computer interfaces and their applications for rehabilitation, robotics and control of human brain states

AE Hramov, VA Maksimenko, AN Pisarchik - Physics Reports, 2021‏ - Elsevier
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 …

A tutorial for information theory in neuroscience

NM Timme, C Lapish - eneuro, 2018‏ - eneuro.org
Understanding how neural systems integrate, encode, and compute information is central to
understanding brain function. Frequently, data from neuroscience experiments are …

A multivariate approach for patient-specific EEG seizure detection using empirical wavelet transform

A Bhattacharyya, RB Pachori - IEEE Transactions on …, 2017‏ - ieeexplore.ieee.org
Objective: This paper investigates the multivariate oscillatory nature of
electroencephalogram (EEG) signals in adaptive frequency scales for epileptic seizure …

Visual and kinesthetic modes affect motor imagery classification in untrained subjects

P Chholak, G Niso, VA Maksimenko, SA Kurkin… - Scientific reports, 2019‏ - nature.com
The understanding of neurophysiological mechanisms responsible for motor imagery (MI) is
essential for the development of brain-computer interfaces (BCI) and bioprosthetics. Our …

Extreme value theory inspires explainable machine learning approach for seizure detection

OE Karpov, VV Grubov, VA Maksimenko, SA Kurkin… - Scientific Reports, 2022‏ - nature.com
Epilepsy is one of the brightest manifestations of extreme behavior in living systems.
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

VA Maksimenko, SA Kurkin, EN Pitsik, VY Musatov… - …, 2018‏ - Wiley Online Library
We apply artificial neural network (ANN) for recognition and classification of
electroencephalographic (EEG) patterns associated with motor imagery in untrained …

Statistical properties and predictability of extreme epileptic events

NS Frolov, VV Grubov, VA Maksimenko, A Lüttjohann… - Scientific reports, 2019‏ - nature.com
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 …

Absence seizure control by a brain computer interface

VA Maksimenko, S Van Heukelum, VV Makarov… - Scientific Reports, 2017‏ - nature.com
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 …

Open-loop neuroadaptive system for enhancing student's cognitive abilities in learning

VV Grubov, MV Khramova, S Goman, AA Badarin… - IEEE …, 2024‏ - ieeexplore.ieee.org
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 …

Functional networks of the brain: from connectivity restoration to dynamic integration

AE Hramov, NS Frolov, VA Maksimenko… - Physics …, 2021‏ - iopscience.iop.org
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 …