A simple and improved eye movement features detection process from saccadic samples of electrooculographic data

In this manuscript a simple and improved eye movement features detection process is described. As most of human activities involve eyes, eye movement features detection is very important, particularly in ubiquitous computing and smart human computer interfaces. We all are familiar with Eye movement features detection techniques that involves image or video processing. But in this work we concentrated on a relatively new eye movement features detection technique that uses electrostatic potential from eyes, also known as Electrooculography signal. The work includes the detailed signal processing steps necessary to detect the various eye movement features from the raw Electrooculography signal. The detection process is simple and improved compared to previous counterparts. The detection process is user independent and thus free of any calibration problems.