Brain Computer Interfaces (BCI)

Brain computer interfaces (BCIs) are an exciting way to control a device. After a number of decades of research and many improvements particularly made in recent years, we are still far away from having BCI applications used for daily tasks. Mainly they are applied for medical purposes and in research. One reason for this are their still very limited capabilities, far lower than those of common human device interfaces like button-based, touch-based, voice-recognition-based, or gesture recognition based interfaces. However, opposed to these, BCIs have one really smart property: They are the only known human device interfaces that do not involve any muscle actions. Therefore, BCIs are mostly beneficial to people, who lost the control over all

Which opportunities could a BCI provide? Let us assume we have an autonomous wheelchair, which already has the capability to navigate on itself and find its path to a given goal. In order to command it to a certain goal, different means of input have been added. As there are voice, the use of a game controller, or a control stick. For highly disabled people, nonetheless, these interfaces are of no use. They would need something they could use without muscle movements they would need a BCI (Jiang, Tham, Yeo, & Phu, 2012).
With that, such people would recover a part of their independence in mobility through the wheelchair. Through the BCI they would achieve the ability to command. And that would be, of course, not limited to that wheelchair. It could easily be prolonged to an arbitrary computerized device. That would be a huge assistance.
Further, in this section the work’s background is presented, as well as the problem to solve, related work, its goal and requirements to fulfil, and lastly, a short overview over the structure of BCIs is

What if our brain starts directing devices? It sounds like fiction, but over the past decade, many laboratories have begun to explore brain–computer interface (BCI) technology. It is a new communication option for those, with neuromuscular impairments, which prevent them from using conventional augmentative communication methods (Raajan & Jayabhavani, 2013). Due to the difficulty of extracting useful information from brain electrical or magnetic field measurements, sensitive analytic methods are often required. Different types of brain signal could be available based on different situations (Blankertz, Tomioka, Lemm, Kawanabe, & M??ller, 2008). The importance of Brain Computer Interface (BCI) is being increased day by day due to its application(Jiang et al., 2012). Some researchers have already successfully implemented this technology in various bio-medical applications, such as exoskeletons, robots and artificial limbs. They developed different control algorithms based on BCI using complex signal processing