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 …
Physical principles of brain–computer interfaces and their applications for rehabilitation, robotics and control of human brain states
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 …
review the physical principles of BCIs, and underlying novel approaches for registration …
Summary of over fifty years with brain-computer interfaces—a review
Over the last few decades, the Brain-Computer Interfaces have been gradually making their
way to the epicenter of scientific interest. Many scientists from all around the world have …
way to the epicenter of scientific interest. Many scientists from all around the world have …
Immediate and long-term effects of BCI-based rehabilitation of the upper extremity after stroke: a systematic review and meta-analysis
Background A substantial number of clinical studies have demonstrated the functional
recovery induced by the use of brain-computer interface (BCI) technology in patients after …
recovery induced by the use of brain-computer interface (BCI) technology in patients after …
Passive BCI beyond the lab: current trends and future directions
Over the last decade, passive brain–computer interface (BCI) algorithms and biosignal
acquisition technologies have experienced a significant growth that has allowed the real …
acquisition technologies have experienced a significant growth that has allowed the real …
[HTML][HTML] Hybrid brain–computer interface techniques for improved classification accuracy and increased number of commands: a review
In this paper, hybrid brain-computer interface (hBCI) technologies for improving
classification accuracy and increasing the number of commands are reviewed. Hybridization …
classification accuracy and increasing the number of commands are reviewed. Hybridization …
A novel hybrid deep learning scheme for four-class motor imagery classification
R Zhang, Q Zong, L Dou, X Zhao - Journal of neural engineering, 2019 - iopscience.iop.org
Objective. Learning the structures and unknown correlations of a motor imagery
electroencephalogram (MI-EEG) signal is important for its classification. It is also a major …
electroencephalogram (MI-EEG) signal is important for its classification. It is also a major …
Diversity and suitability of the state-of-the-art wearable and wireless EEG systems review
Wireless electroencephalography (EEG) systems have been attracting increasing attention
in recent times. Both the number of articles discussing wireless EEG and their proportion …
in recent times. Both the number of articles discussing wireless EEG and their proportion …
Fully portable and wireless universal brain–machine interfaces enabled by flexible scalp electronics and deep learning algorithm
Variation in human brains creates difficulty in implementing electroencephalography into
universal brain–machine interfaces. Conventional electroencephalography systems typically …
universal brain–machine interfaces. Conventional electroencephalography systems typically …
Brain-computer interfaces: Definitions and principles
Throughout life, the central nervous system (CNS) interacts with the world and with the body
by activating muscles and excreting hormones. In contrast, brain-computer interfaces (BCIs) …
by activating muscles and excreting hormones. In contrast, brain-computer interfaces (BCIs) …