A potential limitation of a motor imagery (MI) based brain-computer interface (BCI) is that it
usually requires a relatively long time to record sufficient electroencephalogram (EEG) data …

Motor imagery (MI) decoding is an important part of brain-computer interface (BCI) research,
which translates the subject's intentions into commands that external devices can execute …

Although brain-computer interface (BCI) techniques have been develo** quickly in recent
decades, there still exist a number of unsolved problems, such as improvement of motor …

The objective of this study is to develop a reliable and robust analysis system that can
automatically detect motor imagery (MI) based electroencephalogram (EEG) signals for the …

Objective: A challenging task for an electroencephalography (EEG)-based asynchronous
brain-computer interface (BCI) is to effectively distinguish between the idle state and the …

Motor imagery brain-computer interface (BCI) systems require accurate and fast recognition
of brain activity patterns for reliable communication and interaction. Achieving this accuracy …

Abstract Background Brain Computer Interface (BCI) systems have been widely used to
develop sustainable assistive technology for people suffering from neurological …

The translation of brain activities into signals in brain–computer interface (BCI) systems
requires a robust and accurate classification to develop a communication system for motor …

In off-line training of motor imagery-based brain-computer interfaces (BCIs), to enhance the
generalization performance of the learned classifier, the local information contained in test …

This study focuses on the identification of Motor Imagery (MI) tasks for the development of
Brain Computer Interface (BCI) technologies combining Cross-Correlation and Logistic …