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 …

Brain-machine interfaces: from basic science to neuroprostheses and neurorehabilitation

MA Lebedev, MAL Nicolelis - Physiological reviews, 2017 - journals.physiology.org
Brain-machine interfaces (BMIs) combine methods, approaches, and concepts derived from
neurophysiology, computer science, and engineering in an effort to establish real-time …

Depression biomarkers using non-invasive EEG: A review

FS de Aguiar Neto, JLG Rosa - Neuroscience & Biobehavioral Reviews, 2019 - Elsevier
Depression is a serious neurological disorder characterized by strong loss of interest,
possibly leading to suicide. According to the World Health Organization, more than 300 …

Brain–computer interface spellers: A review

A Rezeika, M Benda, P Stawicki, F Gembler, A Saboor… - Brain sciences, 2018 - mdpi.com
A Brain–Computer Interface (BCI) provides a novel non-muscular communication method
via brain signals. A BCI-speller can be considered as one of the first published BCI …

Transfer learning for EEG-based brain–computer interfaces: A review of progress made since 2016

D Wu, Y Xu, BL Lu - IEEE Transactions on Cognitive and …, 2020 - ieeexplore.ieee.org
A brain–computer interface (BCI) enables a user to communicate with a computer directly
using brain signals. The most common noninvasive BCI modality, electroencephalogram …

Transfer learning: A Riemannian geometry framework with applications to brain–computer interfaces

P Zanini, M Congedo, C Jutten, S Said… - IEEE Transactions …, 2017 - ieeexplore.ieee.org
Objective: This paper tackles the problem of transfer learning in the context of
electroencephalogram (EEG)-based brain-computer interface (BCI) classification. In …

A major depressive disorder classification framework based on EEG signals using statistical, spectral, wavelet, functional connectivity, and nonlinear analysis

RA Movahed, GP Jahromi, S Shahyad… - Journal of Neuroscience …, 2021 - Elsevier
Background Major depressive disorder (MDD) is a prevalent mental illness that is diagnosed
through questionnaire-based approaches; however, these methods may not lead to an …

Data augmentation for deep neural networks model in EEG classification task: a review

C He, J Liu, Y Zhu, W Du - Frontiers in Human Neuroscience, 2021 - frontiersin.org
Classification of electroencephalogram (EEG) is a key approach to measure the rhythmic
oscillations of neural activity, which is one of the core technologies of brain-computer …

Manifold embedded knowledge transfer for brain-computer interfaces

W Zhang, D Wu - IEEE Transactions on Neural Systems and …, 2020 - ieeexplore.ieee.org
Transfer learning makes use of data or knowledge in one problem to help solve a different,
yet related, problem. It is particularly useful in brain-computer interfaces (BCIs), for co** …

Affective brain–computer interfaces (abcis): A tutorial

D Wu, BL Lu, B Hu, Z Zeng - Proceedings of the IEEE, 2023 - ieeexplore.ieee.org
A brain–computer interface (BCI) enables a user to communicate directly with a computer
using only the central nervous system. An affective BCI (aBCI) monitors and/or regulates the …