Recent research has reached a consensus on the feasibility of motor imagery brain-
computer interface (MI-BCI) for different applications, especially in stroke rehabilitation. Most …

A review of physical and mathematical methods for reconstructing the functional networks of
the brain based on recorded brain activity is presented. Various methods are considered, as …

Brain-machine interfaces (BMIs) can be used to decode brain activity into commands to
control external devices. This paper presents the decoding of intuitive upper extremity …

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 …

A major challenge in motor imagery (MI) of electroencephalogram (EEG) based brain–
computer interfaces (BCIs) is the individual differences for different people. That the …

An important challenge in developing a movement-related cortical potential (MRCP)-based
brain-machine interface (BMI) is an accurate decoding of the user intention for real-world …

Brain-computer interface (BCI) has become extremely popular in recent decades. It gained
its significance from the intention of helping paralyzed people communicate with the external …

Decoding of motor imagery (MI) from Electroencephalogram (EEG) is an important
component of BCI system that helps motor-disabled people interact with the outside world …

It is difficult to identify optimal cut-off frequencies for filters used with the common spatial
pattern (CSP) method in motor imagery (MI)-based brain-computer interfaces (BCIs). Most …

In this work, we propose a novel brain-controlled wheelchair, one of the major applications
of brain-machine interfaces (BMIs), that allows an individual with mobility impairments to …