Features Extraction of EOG for handicapped

Making a connection between eye and computer in order to control the side equipments are broadly studied in recent decades. This science can be used as a connection between human and computer because of recent improvements in case of signals and accurate tools. Face is the most important parts of the body. You can sense or express communicative messages so it’s considered as an interface for interchanging information. Its muscles used for producing sound, chewing and motion and also act as an index that shows one’s feelings. According to the above contexts, face is a highly informative source that helps you to extract those signals like eye motion electric (EOG)1, brain electric activity (EEG)2, forehead part and temple, electric activity and feeling scales (EMG)3. How do vision signal function ? Record the (EOG) signal, disporting the canals, extract the features, filter and using the results for controlling the tools. In the signal recording step (EOG), the other vital body signals such as ECG, EMG, EEG and city electric noise and environmental factors act effectively. Features extraction4 is a kind of process that determines the sensible features by doing some operations on data. In this study, we extract seven features such as average, mean, mode, maximum, minimum, variation domain and scale deviation. The purposeof this study is making the data useful for using them later.

Keywords:

Electriiculogram (EOG) , Electromyography (EEG) , VISION SIGNAL , Disparting canals , Feature extraction