[HTML][HTML] A review of the role of machine learning techniques towards brain–computer interface applications

S Rasheed - Machine Learning and Knowledge Extraction, 2021 - mdpi.com
This review article provides a deep insight into the Brain–Computer Interface (BCI) and the
application of Machine Learning (ML) technology in BCIs. It investigates the various types of …

Developments in the human machine interface technologies and their applications: a review

HP Singh, P Kumar - Journal of medical engineering & technology, 2021 - Taylor & Francis
Human-machine interface (HMI) techniques use bioelectrical signals to gain real-time
synchronised communication between the human body and machine functioning. HMI …

EEG-based BCI and video games: a progress report

B Kerous, F Skola, F Liarokapis - Virtual Reality, 2018 - Springer
This paper presents a systematic review of electroencephalography (EEG)-based brain–
computer interfaces (BCIs) used in the video games, a vibrant field of research that touches …

[HTML][HTML] A motion-classification strategy based on sEMG-EEG signal combination for upper-limb amputees

X Li, OW Samuel, X Zhang, H Wang, P Fang… - … of neuroengineering and …, 2017 - Springer
Background Most of the modern motorized prostheses are controlled with the surface
electromyography (sEMG) recorded on the residual muscles of amputated limbs. However …

Network-based brain–computer interfaces: principles and applications

J Gonzalez-Astudillo, T Cattai… - Journal of neural …, 2021 - iopscience.iop.org
Brain–computer interfaces (BCIs) make possible to interact with the external environment by
decoding the mental intention of individuals. BCIs can therefore be used to address basic …

Longitudinal evaluation of EEG-based biometric recognition

E Maiorana, P Campisi - IEEE transactions on Information …, 2017 - ieeexplore.ieee.org
Brain signals have recently attracted the attention of the scientific community as potential
biometric identifiers. In more detail, there is a growing interest in evaluating the feasibility of …

[HTML][HTML] Computational models in electroencephalography

K Glomb, J Cabral, A Cattani, A Mazzoni, A Raj… - Brain topography, 2022 - Springer
Computational models lie at the intersection of basic neuroscience and healthcare
applications because they allow researchers to test hypotheses in silico and predict the …

Does ipsilateral remapping following hand loss impact motor control of the intact hand?

R Tucciarelli, N Ejaz, DB Wesselink, V Kolli… - Journal of …, 2024 - Soc Neuroscience
What happens once a cortical territory becomes functionally redundant? We studied
changes in brain function and behavior for the remaining hand in humans (male and female) …

A Survey of EEG and Machine Learning based methods for Neural Rehabilitation

J Singh, F Ali, R Gill, B Shah, D Kwak - IEEE Access, 2023 - ieeexplore.ieee.org
One approach to therapy and training for the restoration of damaged muscles and motor
systems is rehabilitation. EEG-assisted Brain-Computer Interface (BCI) may assist in …

Classification of EEG signals for brain-computer interface applications: Performance comparison

MZ Ilyas, P Saad, MI Ahmad… - … Conference on Robotics …, 2016 - ieeexplore.ieee.org
This paper presents a comparison of Electroencephalogram (EEG) signals classification for
Brain Computer-Interfaces (BCI). At present, it is a challenging task to extract the meaningful …