Analysis of EOG Signals Using Empirical Mode Decomposition for Eye Blink Detection

Abstract

Eye ball movement is the most common way for paralysis patients to communicate. Eye movement can be used by the paralysis patients and armless persons to perform simple tasks such as Human Machine Interfacing and EOG signals are also vital signs in some of the neurological disorders and it can be tracked by acquiring electrooculogram (EOG) . EOG is an obtrusive, inexpensive and non-invasive means of recording eye ball movements. The source for EOG signal is cornea-retinal potential (CRP) and is generated due to the movements of eye balls within the conductive environment of the skull. While recording the EOG signal, it will be contaminated by electromyography (EMG) signal. As the EOG is a non stationary signal like other biomedical signals ECG, EEG & PPG. Generally they are suffers from different interferences like power line interference and with other biomedical signals. The concept of decomposing the signal into different IMF's will analyze the EOG signals to study different types of eye movements (SEMs & REMs). In this paper, the well established method is utilized for denoising and detection of eye blinks from ECG signals.