Noninvasive electroencephalography equipment for assistive, adaptive, and rehabilitative brain–computer interfaces: a systematic literature review

N Jamil, AN Belkacem, S Ouhbi, A Lakas - Sensors, 2021 - mdpi.com
Humans interact with computers through various devices. Such interactions may not require
any physical movement, thus aiding people with severe motor disabilities in communicating …

Comprehensive review on brain-controlled mobile robots and robotic arms based on electroencephalography signals

M Aljalal, S Ibrahim, R Djemal, W Ko - Intelligent service robotics, 2020 - Springer
There is a significant progress in the development of brain-controlled mobile robots and
robotic arms in the recent years. New advances in electroencephalography (EEG) …

A large electroencephalographic motor imagery dataset for electroencephalographic brain computer interfaces

M Kaya, MK Binli, E Ozbay, H Yanar, Y Mishchenko - Scientific data, 2018 - nature.com
Recent advancements in brain computer interfaces (BCI) have demonstrated control of
robotic systems by mental processes alone. Together with invasive BCI …

Critic learning-based control for robotic manipulators with prescribed constraints

Y Ouyang, L Dong, C Sun - IEEE Transactions on Cybernetics, 2020 - ieeexplore.ieee.org
In this article, the optimal control problem for robotic manipulators (RMs) with prescribed
constraints is addressed. Considering the environmental conditions and requirements of …

Cybersecurity in neural interfaces: Survey and future trends

X Jiang, J Fan, Z Zhu, Z Wang, Y Guo, X Liu… - Computers in Biology …, 2023 - Elsevier
With the joint advancement in areas such as pervasive neural data sensing, neural
computing, neuromodulation and artificial intelligence, neural interface has become a …

Imaginary finger movements decoding using empirical mode decomposition and a stacked BiLSTM architecture

T Mwata-Velu, JG Avina-Cervantes, JM Cruz-Duarte… - Mathematics, 2021 - mdpi.com
Motor Imagery Electroencephalogram (MI-EEG) signals are widely used in Brain-Computer
Interfaces (BCI). MI-EEG signals of large limbs movements have been explored in recent …

Evaluation of mother wavelets on steady-state visually-evoked potentials fortriple-command brain-computer interfaces

E Sayilgan, YK Yüce, Y İŞLER - Turkish Journal of Electrical …, 2021 - journals.tubitak.gov.tr
Wavelet transform (WT) is an important tool to analyze the time-frequency structure of a
signal. The WT relies on a prototype signal that is called the mother wavelet. However, there …

Recognition of upper limb action intention based on IMU

JW Cui, ZG Li, H Du, BY Yan, PD Lu - Sensors, 2022 - mdpi.com
Using motion information of the upper limb to control the prosthetic hand has become a
hotspot of current research. The operation of the prosthetic hand must also be coordinated …

Motor imagery classification via kernel-based domain adaptation on an SPD manifold

Q Jiang, Y Zhang, K Zheng - Brain Sciences, 2022 - mdpi.com
Background: Recording the calibration data of a brain–computer interface is a laborious
process and is an unpleasant experience for the subjects. Domain adaptation is an effective …

Subject-independent trajectory prediction using pre-movement EEG during grasp and lift task

A Jain, L Kumar - Biomedical Signal Processing and Control, 2023 - Elsevier
Electroencephalogram (EEG) based motor trajectory decoding for efficient control of brain–
computer interface (BCI) systems has been an active area of research. The systems include …