Communication, neuro-prosthetics, and environmental control are just a few applications for
disabled persons who use robots and manipulators that use brain-computer interface (BCI) …

With the development of the brain-computer interface (BCI) community, motor imagery-
based BCI system using electroencephalogram (EEG) has attracted increasing attention …

The effect of early fault vibration signals from rotating machinery is weak and easily drowned
out by intense noise. Therefore, it is still a great challenge to make early fault diagnosis. An …

Multi-channel electroencephalography (EEG) is used to capture features associated with
motor imagery (MI) based brain-computer interface (BCI) with a wide spatial coverage …

Currently, steady-state visual evoked potentials (SSVEPs) are applied in a variety of fields.
In these applications, spatial filtering is the most commonly used method for decoding …

In brain computer interface-based neurorehabilitation system, a large number of electrodes
may increase the difficulty of signal acquisition and the time consumption of decoding …

Recently, sparse representation-based classification has turned into a successful technique
for motor imagery electroencephalogram signal analysis. In this approach, the data is …

Brain fingerprint with electroencephalogram (EEG) is widely employed in identification.
However, the security of brain fingerprint and the identification system is greatly reduced due …

This study describes a novel entrainment loss monitoring system. The features of the
collision signals of different maize materials were extracted in the time and frequency …

Motor Imagery (MI) based brain-computer interface (BCI) systems are used for regaining the
motor functions of neurophysiologically affected persons. But the performance of MI tasks is …