Abstract — There are numerous people in the world who suffer from disabilities that prevent them from using traditional means to control a computer. Alternative forms of input are needed for these people. One potential input device is an electroencephalography machine that can be used to detect patterns of brain activity and use these patterns to trigger events on a computer such as mouse clicks or keyboard presses. This allows those who don't use their hands to be able to control a computer without invasive surgery.I. INTRODUCTIONElectroencephalography or EEG is a technique that uses electrodes to detect and amplify the electrical potential that corresponds to the activation of neurons in the brain. Although each neuron produces its own signal when it fires, it is nearly impossible to detect the activity of a single neuron via EEG. Instead, activating thousands of neurons in a pattern produces a signal strong enough to be picked up via electrodes placed on the scalp. These models can be used to analyze and diagnose mental conditions such as epilepsy, to monitor and observe the brain's responses to external stimuli, or as a potential means of hands-free control over a system.Fig. 1 One second of the EEG signal [2]Clinical electroencephalographic devices use a particular electrode placement known as the "International 10-20 System for Electrode Placement", or simply the 10-20 system. This method was developed to standardize the placement of electrodes on the scalp so that studies could be easily reproduced. The name comes from the fact that the distance between the electrodes is 10% or 20% apart from each other. The layout of the 10-20 system is shown in Figure 1.Fig. 2 The 10...... half of the sheet ......d. 2006. Print.[2] Wikipedia. (nd) Electroencephalography. Retrieved May 11, 2009 from Wikipedia: http://en.wikipedia.org/wiki/Electroencephalography[3] Kayagil, Turan A., Bai, Ou, Henriquez, Craig S., Lin, Peter, Furlani, Stephen J. , Vorbach, Sherry, Hallett, Mark, “A binary method for simple and accurate two-dimensional cursor control from EEG with minimal subject training” in Journal of NeuroEngineering and Rehabilitation, 2009, vol. 6, no. 14.[4] Ferreira, Andre, Celeste, Wanderly C., Cheein, Fernando A., Bastos-Filho, Teodiano F., Sarcinelli-Filho, Mario, Carelli, Ricardo, “Human-machine interfaces based on EMG and EEG applied to robotic systems” in Journal of Neuroengineering and Rehabilitation, 2008, vol. 5, no. 10.[5] WisBusiness, “UW-Madison: Researchers Use Brain Interface to Post to Twitter,” http://www.wisbusiness.com/index.Iml?Article=156008