**1. Introduction**

The spontaneous electrical currents in mammalian brain (rabbit and monkey) were first demonstrated by English Physiologist Richard Caton in 1870s, but the human electroencephalogram (EEG) was discovered in 1924 by German Psychiatrist Hans Berger [1]. The brain waves (neural oscillations) can be considered as biomarkers for wide range of applications from therapeutic to cognitive disorders [2]. The neural activities in brain generate voltages in response to external events or stimuli called event potential (EP). However, event-related desynchronization/synchronization (ERD/ERS) does not require such external stimulation.

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Interestingly, EP components can be subdivided into steady-state evoked potential (SSEP) and event-related potential (ERP), and ERD/ERS from motor imagination. Eventually, there are three main approaches employed by researchers to study electric signals generated from the brain activities. Following sections will elaborate discussion about these approaches.

target character is selected at first level and the target is selected at second level which elicits P300. The number of characters in the RB speller is 49 and the probability of hitting a target is 1/7 which evokes higher amplitude of P300. Thus, accuracy, user acceptability, and ITR are

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Only one character flashes in single character (SC) paradigm rather than all the six characters in row or column in RC paradigm [8]. In [9], SC paradigm was compared with RC paradigm for 19 subjects and observed that the classification accuracy was better for RC (85.3%) than SC (77.90%). Further, in [10], four P300 BCI spellers: RC, SC and two RB paradigms were compared, in which characters were based on alphabetical order in one and frequency of use in another. It was observed that accuracy of RB with characters in alphabetical order was highest and SC, the least for six subjects to spell two words WATER and LUCAS in three trials. In addition, whereas, user acceptability was highest for both RB paradigms than RC and SC, and

A checker board (CB) paradigm was proposed in [11], having 8×9 matrix of alphanumeric characters and keyboard commands, and compared the performance with traditional RC paradigm. Eighteen healthy subjects were used for the experiment and it was found that mean online accuracy, mean bit rate, and user acceptability were significantly higher for CB than RC but it suffers from adjacency errors. Other various modifications on standard RC paradigm have been done like a constant character flashing and shape changing which enhances the

The concept of visual evoked potential (VEP) was given by [13] using flash light and calculated evoked EEG signal by averaging to measure visual evoked responses from four parietal and occipital regions of scalp with bipolar electrodes. A clear high amplitude plot after 80 and 145 ms of the stimulus was found. VEPs, due to low stimulus rates, are classified as transient VEPs (TVEPs) and the repetitive high stimulations are under steady-state VEPs (SSVEPs). TVEP responses are during brain resting stage and if visual stimuli duration is shorter, evoked responses by each stimulus overlap each other and SSVEP is generated at

SSVEP based on gaze detection falls into dependent BCI and is not suitable for ALS patients who cannot move their eyes. Gaze-independent SSVEP using LED interlaced square pattern for stimulation has been designed by [16]. People can shift attention among visual stimuli without shifting gaze, called as covert attention and overlapping stimuli can evoke changes in SSVEP which is sufficient to control BCI without gaze shifting like two overlapped images. Training for selective attention like playing certain types of computer games can improve SSVEP performance, and SSVEP systems are suitable to operate in challenging environments

SSVEP visual stimuli are three main types as categorized below among which LED stimulation results in highest bit rate. All visual stimuli have properties like frequency, color, and contrast which affect SSVEP. Stimuli frequency can be divided into low (1–12 Hz),

enhanced in RB paradigm than traditional RC paradigm [6].

region accuracy was least for central character on seven regions [6].

performances of P300 to some extent [12].

**1.2. Steady-state visual evoked potential**

steady state of brain excitation [14, 15].

with distractions and noises like in homes and hospitals [17].
