Multifractal Behavior of the Electrooculography Signal

6th INTERNATIONAL CONFERENCE ON GLOBAL PRACTICE OF MULTIDISCIPLINARY SCIENTIFIC STUDIES, 9 - 16 April 2024, vol.1, pp.1786-1798

The aim of this study is to examine the multi-fractal behavior of the electrooculography (EOG)

signal, which is an eye movement recording technique based on electrical activity originating

from the eyes. For this purpose, the method called multifractal detrended fluctuation analysis

is used, which can determine the multi-fractal spectrum of power law exponents from the

electrooculography time series. Electrooculography is a biomedical signal that can be used to

improve human-computer interfaces. Structural features of biomedical signals are often

visually evident, but these structural features cannot be captured by traditional measurements

such as the average amplitude of the signal. A biomedical signal has a scale-invariant structure

when structures in subranges of the signal repeat themselves. Fractal analysis estimates the

power law exponent that describes certain types of scale-invariant structure of the biomedical

signal. Fractal analyzes are frequently used in biomedical signal processing (ECG, EEG, MR

and X-ray images) to define the scale-independent invariant structure of the signal. Fractal

analysis enables the discrimination between healthy and pathological conditions by using the

scale-invariant structures of the interval between action potentials of nerve cells, the interval

between steps of human walking, the interval between breaths of human respiration and the

intervals between beats of the human heart. However, spatial and temporal differences in the

scale-invariant structure of biomedical signals often occur. These spatial and temporal

variations indicate a multi-fractal structure of the biomedical signal defined by a multifractal

spectrum of power law exponents. The monofractal and multifractal structures of the

biomedical signal are invariant structures at a certain scale. Most commonly, the monofractal

structure of biomedical signals is described by a single power-law exponent and assumes scale

invariance to be independent of time and space. However, spatial and temporal differences in

the scale-invariant structure of the biomedical signal often occur. These spatial and temporal

variations indicate a structure of the biomedical signal defined by a multifractal spectrum of

power law exponents. In this study, the EOG signal taken from human subjects is examined by

the multifractal detrended fluctuation analysis method at various scales and the multifractal

structure of the EOG signal is shown.