Abstract Brain–computer interfaces (BCIs), representing a transformative form of human–
computer interaction, empower users to interact directly with external environments through …

Motor imagery (MI) is an important brain-computer interface (BCI) paradigm. The traditional
MI paradigm (imagining different limbs) limits the intuitive control of the outer devices, while …

Develo** efficient algorithms harnessing the power of current quantum processors has
sparked the emergence of techniques that combine soft computing with quantum computing …

Brain–computer interfaces (BCIs) based on motor imagery (MI) enable the disabled to
interact with the world through brain signals. To meet demands of real-time, stable, and …

This paper explores the parallel collaboration of multimodal physiological signals,
combining eye tracker output signals, motor imagery, and error-related potentials to control a …

Brain–computer interfaces, where motor imagery electroencephalography (EEG) signals are
transformed into control commands, offer a promising solution for enhancing the standard of …

Objective. Motor imagery-based brain–computer interaction (MI-BCI) is a novel method of
achieving human and external environment interaction that can assist individuals with motor …

Motor imagery-based brain-computer interface (MI-BCI) systems convert user intentions into
computer commands, aiding the communication and rehabilitation of individuals with motor …

Accurate recognition and classification of motor imagery electroencephalogram (MI-EEG)
signals are crucial for the successful implementation of brain-computer interfaces (BCI) …

This paper presents an advanced approach for EEG artifact removal and motor imagery
classification using a combination of Four Class Iterative Filtering and Filter Bank Common …