The aim of this paper is to lay a foundation for providing a soft algebraic tool in considering many problems that contain uncertainties. In order to provide these soft algebraic structures, the notions of closed intersectional soft BCI-ideals and intersectional soft commutative BCI-ideals are introduced, and related properties are investigated. Conditions for an intersectional soft BCI-ideal t...

OBJECTIVE Implantable brain-computer interface (BCI) research promises improvements in human health and enhancements in quality of life. Informed consent of subjects is a central tenet of this research. Rapid advances in neuroscience, and the intimate connection between functioning of the brain and conceptions of the self, make informed consent particularly challenging in BCI research. Identifi...

Moving a brain-computer interface (BCI) system from a laboratory demonstration to real-life applications still poses severe challenges to the BCI community. This study aims to integrate a mobile and wireless electroencephalogram (EEG) system and a signal-processing platform based on a cell phone into a truly wearable and wireless online BCI. Its practicality and implications in a routine BCI ar...

Brain-computer interfaces (BCIs) have widely been used in medical applications, to facilitate making selections. However, whether they are suitable for recreational applications is unclear as they have rarely been evaluated for user experience. As the scope of the BCI applications is expanding from medical to recreational use, the expectations of BCIs are also changing. Although the performance...

An error potential (ErrP) is an innate event-related potential generated when a subject makes a mistake, and, more relevant to brain-computer interface (BCI) applications, when the BCI itself behaves differently from the user intent. For this reason, error potentials are nowadays attracting attention in the BCI field and the presence of ErrPs has been studied already in a few BCI paradigms. In ...

The high dependency of the Brain Computer Interface (BCI) system performance on the BCI user is a wellknown issue of many BCI devices. This contribution presents a new way to overcome this problem using a synergy between a BCI device and an EEG-based biometric algorithm. Using the biometric algorithm, the BCI device automatically identifies its current user and adapts parameters of the classifi...

Multi-modal techniques have received increasing interest in the neuroscientific and brain computer interface (BCI) communities in recent times. Two aspects of multi-modal imaging for BCI will be reviewed. First, the use of recordings of multiple subjects to help find subject-independent BCI classifiers is considered. Then, multi-modal neuroimaging methods involving combined electroencephalogram...

Abstract— The BCI research has now witnessed incredible expansion using invasive and noninvasive methods but especially the use of Electroencephalogram (EEG) signals (method of non-invasive BCI) has attained a lot of significance. The applications of EEG based BCI ranges from medicine to entertainment. In this paper, a general Electro-Encephalogram (EEG) based BCI system is discussed. Thus deve...