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\section{Review of Related Literature}  \subsection{Related Studies on Electromyography} Electromyography in Computer Science}  According to \cite{elamvazuthi2015development} electromyography or EMG measures the response or electrical activity which occurs when a muscle's nerve is simulated. There are currently two types of EMG: Surface and Intramuscular EMG. Intramuscular EMG deals with the usage of hypodermic needles which are inserted directly into the muscle so surface EMG will be the main focus of this paper. EMG is relevant and useful because sometimes the traditional input method of touch screens and keys are impractical and inadequate. This is prevalent in rigorous activities such as jogging, cycling, or in special cases, simply walking. To address the impracticality of traditional keys in certain situations, alternative input techniques such as EMG, computer vision, and speech recognition.  But, why would EMG be used instead of other input techniques such as computer vision or speech recognition? As stated by \cite{Saponas_2010}, occlusion and lighting limit the capabilities of computer vision and speech recognition may be socially awkward in most situations. To further strengthen the usage of EMG, Saponas stated that the EMG approach "allows people to use their fingers for input without any sensing technology on or near their hands."  
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find source  \end{comment}    EMG has been applied to a variety of fields. The most notable applications are in medicine. EMG has been used to rehabilitate stroke victims \cite{Viriyasaksathian_2011}, provide computer access for people who are unable to use a mouse, trackpad, touchpad, or keyboard \cite{Craig_Chin}, and control prosthetic hands more dexterously \cite{Al_Timemy_2013}. Another field is in Game Development and in Computer Science. Development.  This will be further explained in the next section. \subsection{Related Studies on EMG used based gestures  in Computer Science} Science games}  In the game industry, EMG technology has been widely used to replace physical components, such as the traditional joysticks and keyboards with something virtual. In a study conducted by Wheeler and Jorgensen \cite{Wheeler_2003}, it has been understood that there are two forms of most used gesture-recognition systems for receiving inputs. First is through image processing with an external camera as the source of input. Second is through muscle sensors such as the wearable dry-electrode sleeve device they have developed to sense EMG signal as computer inputs. These EMG electrodes work by detecting skin currents with a very low-impendence connection with the skin. It receives the currents that travel in the muscle fiber from the innervation point to the end of the muscle. This device was tested using a virtual number pad and in their case, the participant had to be extra careful and precise with each movement because of the sensitivity and difficulty of distinguishing the keys that were hit.  As mentioned above, another gesture-recognition system is image processing through an external camera. In the study performed by Rautaray et al. \cite{Rautaray_2011}, various image processing techniques were applied for hand tracking and gesture recognition in a virtual gaming environment such as Camshift, Lucas Kanade, Haar etc. The different gestures used for the game interactions were grab, punch and go.