Neurofeedback (NF) and brain-computer interface (BCI) applications rely on the registration
and real-time feedback of individual patterns of brain activity with the aim of achieving self …

Context. In recent years, hybrid brain-computer interfaces (hBCIs) have proven to be a
promising path towards practical brain-computer interfacing. These hybrid interfaces …

Background Common spatial pattern (CSP) has been most popularly applied to motor-
imagery (MI) feature extraction for classification in brain–computer interface (BCI) …

Objective: Tactile brain-computer interface (BCI) systems can provide new communication
and control options for patients with impairments of eye movements or vision. One of the …

Despite rapid advances in the study of brain–computer interfaces (BCIs) in recent decades,
two fundamental challenges, namely, improvement of target detection performance and …

For cochlear implant users, combined electro-acoustic stimulation (EAS) significantly
improves the performance. However, there are many more users who do not have any …

Objective: This study proposes an event-related potential (ERP) brain-computer interface
(BCI)-based environmental control system that integrates household electrical appliances, a …

Off-the-shelf, consumer-grade EEG equipment is nowadays becoming the first-choice
equipment for many scientists when it comes to recording brain waves for research …

Conventional brain‐computer interface (BCI) systems have been facing two fundamental
challenges: the lack of high detection performance and the control command problem. To …

Empirical mode decomposition (EMD) provides an adaptive, data-driven approach to time–
frequency analysis, yielding components from which local amplitude, phase, and frequency …