EEG (Electroencephalogram) often provides interfaces for controlling machines or computers due to recent developments in inexpensive, easy-to-wear, and low power acquisition systems [1, 2]. Thus, EEG-based Brain Computer Interface (BCI) is one of the most promising technologies for device interaction and detection of cognitive and emotional activities. As a result, abundant studies have been performed to investigate the BCI-based interfaces: event-related synchronization/desynchronization (ERS/ERD), steady-state visual evoked potentials (SSVEP), slow cortical potentials (SCP), visually evoked P300 potentials, movement-related potentials (MRPs), and changes in brain rhythms [3, 4].

However, current EEG-based BCI headsets are ill-suited for daily use owing to challenges with hardware positioning/placement, requisite device knowledge, training, and skills. In fact, the current EEG-based BCI technology usually takes anywhere from a few minutes up to 45 min to configure EEG electrodes on a person’s scalp depending on the types of electrodes (e.g., dry and wet electrodes) used, which is one of major obstacles for the technology to be widely adapted in daily living. Additionally, consumer based EEG headsets have not been widely accepted by the public due to design and their obtrusive nature.