Brain-computer interfaces (BCIs) aim to directly bridge the human brain and the outside
world through acquiring and processing the brain signals in real time. In recent two decades …

Objective. This review paper provides an integrated perspective of Explainable Artificial
Intelligence (XAI) techniques applied to Brain-Computer Interfaces (BCIs). BCIs use …

Motor imagery (MI) is one of the popular control paradigms in the non-invasive brain-
computer interface (BCI) field. MI-BCI generally requires users to conduct the imagination of …

Objective. Transfer learning has become an important issue in the brain-computer interface
(BCI) field, and studies on subject-to-subject transfer within the same dataset have been …

Motor dysfunction is one of the most significant sequelae of stroke, with lower limb
impairment being a major concern for stroke patients. Motor imagery (MI) technology based …

A major goal in neuroscience is to discover neural data representations that generalize. This
goal is challenged by variability along recording sessions (eg environment), subjects (eg …

The MIMED dataset is a dataset that provides raw electroencephalogram signal data for
activities: raising the right-hand, lowering the right-hand, raising the left-hand, lowering the …

The amplitude envelope is a crucial parameter to analyse natural systems as it provides
useful amplitude modulation (AM) based information. In many cases, power spectral entropy …

One of the studies of the active brain-computer interface (BCI) focuses on identifying
movements from human neurophysiological signals to control external devices such as …

The precision of electroencephalograms (EEGs) significantly impacts the performance of
brain–computer interfaces (BCI). Currently, the majority of research into BCI technology …