Common spatial pattern (CSP) technique has been very popular in terms of
electroencephalogram (EEG) features extraction in motor imagery (MI)-based brain …

Lower limb motor imagery (MI) classification is a challenging research topic in the area of
brain-computer interfaces (BCIs), and entails numerous signal channels to provide sufficient …

Precise and timely disease diagnosis is essential for making effective treatment decisions
and halting disease progression. Biomedical signals offer the potential for non-invasive …

In the application of brain-computer interfaces (BCIs), electroencephalogram (EEG) signals
are difficult to collect in large quantities due to the non-stationary nature and long calibration …

Brain-computer interface systems with Electroencephalogram (EEG), especially those use
motor-imagery (MI) signals, have demonstrated the ability to control electromechanical …

Brain-computer interface BCI) is a technology that assists in straight link among the human
brain as well as external devices like computers or robotic systems, without including …

Fault diagnosis is essential for assuring the safety and dependability of rotating machinery
systems. Several emerging techniques, especially artificial intelligence-based technologies …

Nowadays, Electroencephalogram (EEG) devices that do not require invasive procedures
get more attraction. Brain-Computer Interface (BCI) systems use EEG analysis to identify …

Recently, intelligent fault diagnosis based on deep learning has been extensively
investigated, exhibiting state-of-the-art performance. However, the deep learning model is …

One major problem limiting the practicality of a brain-computer interface (BCI) is the need for
large amount of labeled data to calibrate its classification model. Although the effectiveness …