A brain computer interface (BCI) framework uses computer algorithms to detect mental
activity patterns and manipulate external devices. Because of its simplicity and non …

This review article provides a deep insight into the Brain–Computer Interface (BCI) and the
application of Machine Learning (ML) technology in BCIs. It investigates the various types of …

Objective. Modern motor imagery (MI)-based brain computer interface systems often entail a
large number of electroencephalogram (EEG) recording channels. However, irrelevant or …

Classification of electroencephalogram-based motor imagery (MI-EEG) tasks is crucial in
brain–computer interface (BCI). EEG signals require a large number of channels in the …

Recognition of motor imagery intention is one of the hot current research focuses of brain-
computer interface (BCI) studies. It can help patients with physical dyskinesia to convey their …

Classification of electroencephalogram-based motor imagery (MI-EEG) tasks raises a big
challenge in the design and development of brain-computer interfaces (BCIs). In view of the …

Brain–computer interfaces (BCIs) are used to provide a direct communication between the
human brain and the external devices, such as wheelchairs and intelligent apparatus, by …

Fatigue driving has become one of the main causes of traffic accidents, and driving fatigue
detection based on electroencephalogram (EEG) can effectively evaluate the driver's mental …

Abstract Motor Imagery Brain Computer Interface (MI-BCI) has become a promising
technology in the field of neurorehabilitation. However, the performance and computational …

The essential task of a motor imagery brain–computer interface (BCI) is to extract the motor
imagery-related features from electroencephalogram (EEG) signals for classifying motor …