EALab (Eye Activity Lab): a MATLAB Toolbox for Variable Extraction, Multivariate Analysis and Classification of Eye-Movement Data

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EALab (Eye Activity Lab): a MATLAB Toolbox for Variable Extraction, Multivariate Analysis and Classificationof Eye-Movement Data

Javier Andreu-Perez1 & Celine Solnais2 & Kumuthan Sriskandarajah3

Published online: 10 September 2015# Springer Science+Business Media New York 2015

Abstract Recent advances in the reliability of the eye-tracking methodology as well as the increasing availability of affordable non-intrusive technology have opened the door to new research opportunities in a variety of areas and applications. This has raised increasing interest within disciplines such as medicine, business and education for analysing human perceptual and psychological processes based on eye-tracking data. However, most of the currently available software requires programming skills and focuses on the analysis of a limited set of eye-movement measures (e.g., saccades and fixations), thus excluding other measures of interest to the classification of a determined state or condition. This paper describes EALab, a MATLAB toolbox aimed at easing the extraction, multivariate analysis and classification stages of eye-activity data collected from commercial and independent eye trackers. The processing implemented in this toolbox enables to evaluate variables extracted from a wide range of measures including saccades, fixations, blinks, pupil diameter and glissades. Using EALab does not require any programming and the analysis can be performed through a user-friendly graphical user interface (GUI) consisting of three processing modules: 1) eye-activity measure extraction interface,2) variable selection and analysis interface, and 3) classification interface.

Keywords Eye tracking . Machine learning . Multivariate analysis . Classification . Computer software . Neuroinformatics

Introduction

In recent years, the increasing number of non-invasive eye-tracking techniques relying on video-based systems has raised growing interest in eye-movement research. Improvements in the sensing capabilities of pervasive and wearable eye-tracking technology have indeed allowed more natural experimental conditions and enhanced ecological validity. In addition, the availability of affordable devices embedded in monitor screens, glasses and PC peripherals has widened the range of applications offered by the eye-tracking methodology within a variety of disciplines such as medicine, business and education.

Eye tracking provides a valuable source of physiological data regarding the allocation...