CLASSIFICATION OF EYE BEHAVIOR BASED ON ELECTROOCULOGRAM SIGNALS USING LABVIEW TOOLS

Abstract

Today, electrooculogram signals and their relationship with the eye's states
and behaviors have been studying. The research results have been used for many
purposes. Like other types of biomedical signals, electrooculogram signals are
often affected by several types of noise: white noise, high-frequency noise, 50Hz
industrial noise, etc. This paper presents a solution to use LABVIEW
programming tools to acquire, process electrooculogram signals, and classify eye
behavior based on electrooculogram signals. This is also the foundation for
development applications and devices controlled through behavior and vision
state of eyes to support human activities in life such as wheelchair control,
computer mouse control, menu selection or in the system sleep alert system, etc.