Past, present, and future of EEG-based BCI applications
K Värbu, N Muhammad, Y Muhammad - Sensors, 2022 - mdpi.com
An electroencephalography (EEG)-based brain–computer interface (BCI) is a system that
provides a pathway between the brain and external devices by interpreting EEG. EEG …
provides a pathway between the brain and external devices by interpreting EEG. EEG …
[HTML][HTML] A systemic review of available low-cost EEG headsets used for drowsiness detection
J LaRocco, MD Le, DG Paeng - Frontiers in neuroinformatics, 2020 - frontiersin.org
Drowsiness is a leading cause of traffic and industrial accidents, costing lives and
productivity. Electroencephalography (EEG) signals can reflect awareness and …
productivity. Electroencephalography (EEG) signals can reflect awareness and …
Noninvasive electroencephalography equipment for assistive, adaptive, and rehabilitative brain–computer interfaces: a systematic literature review
Humans interact with computers through various devices. Such interactions may not require
any physical movement, thus aiding people with severe motor disabilities in communicating …
any physical movement, thus aiding people with severe motor disabilities in communicating …
Deep neural network for eeg signal-based subject-independent imaginary mental task classification
BACKGROUND. Mental task identification using electroencephalography (EEG) signals is
required for patients with limited or no motor movements. A subject-independent mental task …
required for patients with limited or no motor movements. A subject-independent mental task …
Performance evaluation of EEG/EMG fusion methods for motion classification
Wearable robotic systems have shown potential to improve the lives of musculoskeletal
disorder patients; however, to be used practically, they require a reliable method of control …
disorder patients; however, to be used practically, they require a reliable method of control …
Robotic arm control system based on brain-muscle mixed signals
L Cheng, D Li, G Yu, Z Zhang, S Yu - Biomedical Signal Processing and …, 2022 - Elsevier
Aiming at the existing problems of BCI (brain computer interface), such as single input signal
source, low accuracy of feature recognition, and less output control instructions, this paper …
source, low accuracy of feature recognition, and less output control instructions, this paper …
Classification of mental tasks from EEG signals using spectral analysis, PCA and SVM
Signals provided by the ElectroEncephaloGraphy (EEG) are widely used in Brain-Computer
Interface (BCI) applications. They can be further analyzed and used for thinking activity …
Interface (BCI) applications. They can be further analyzed and used for thinking activity …
Feature stability and setup minimization for EEG-EMG-enabled monitoring systems
Delivering health care at home emerged as a key advancement to reduce healthcare costs
and infection risks, as during the SARS-Cov2 pandemic. In particular, in motor training …
and infection risks, as during the SARS-Cov2 pandemic. In particular, in motor training …
Research progress of rehabilitation exoskeletal robot and evaluation methodologies based on bioelectrical signals
F Wang, X Wei, J Guo, Y Zheng, J Li… - 2019 IEEE 9th Annual …, 2019 - ieeexplore.ieee.org
With the increasing number of elderly and disabled people in China, the rehabilitation
exoskeleton, which integrates sensing, control, information and mobile computing …
exoskeleton, which integrates sensing, control, information and mobile computing …
[PDF][PDF] 混合范式脑-机接口研究进展综述
施文强， 肖晓琳， 刘爽， 许敏鹏， 何峰… - 中国生物医学工程学报, 2022 - cjbme.csbme.org
传统脑-机接口(BCI) 在实际应用中存在许多不足ꎬ 例如指令集较小, 适用人群范围小,
难以实现多维度控制和异步控制等ꎮ 混合范式脑-机接口(hBCI) 的出现可有效解决这些问题ꎮ …
难以实现多维度控制和异步控制等ꎮ 混合范式脑-机接口(hBCI) 的出现可有效解决这些问题ꎮ …