Objective. Biosignal control is an interaction modality that allows users to interact with
electronic devices by decoding the biological signals emanating from the movements or …

In this study, a few-shot transfer learning approach was introduced to decode movement
intention from electroencephalographic (EEG) signals, allowing to recognize new tasks with …

An accurate classification of upper limb movements using electroencephalogram (EEG)
signals is gaining significant importance in recent years due to the prevalence of brain …

Abstract Electroencephalogram (EEG)-based brain–computer interfaces (BCIs) allow users
to use brain signals to control external instruments, and movement intention detecting BCIs …

EEG signals have relatively low spatial resolution (especially for deep brain structures), they
are vulnerable to muscle and eye movement artifacts, and the existing paradigm is difficult to …

Today, the interface between the brain and the computer can be designed using intelligent
tools. This two‐way communication that is named the Brain–computer interface can make …

The loss of limb motion arising from damage to the spinal cord is a disability that could effect
people while performing their day-to-day activities. The restoration of limb movement would …

Abstract Brain Computer Interface (BCI) systems have the potential to provide a
communication tool using non-invasive signals which can be applied to various fields …

Electroencephalogram (EEG) signals, inherently non-stationary and non-linear, present
significant challenges in their processing and interpretation. This paper presents a hybrid …

The ability to organize our movements in well-coordinated and functional sequences that
are flexibly retrieved and generated from memory is a hallmark of the human behavioral …