Andreu-Perez Javier, Solnais Celine, Sriskandarajah Kumuthan
Department of Computing, Imperial College London, London, UK.
Department of Marketing and Market Research, Faculty of Economic and Business Sciences, University of Granada, Granada, Spain.
Neuroinformatics. 2016 Jan;14(1):51-67. doi: 10.1007/s12021-015-9275-4.
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.
眼动追踪方法可靠性方面的最新进展以及价格亲民的非侵入式技术的日益普及,为多个领域和应用带来了新的研究机遇。这引发了医学、商业和教育等学科对基于眼动追踪数据分析人类感知和心理过程的越来越浓厚的兴趣。然而,目前大多数可用软件都需要编程技能,并且侧重于对有限的一组眼动测量指标(如扫视和注视)进行分析,从而排除了对确定状态或情况分类有意义的其他测量指标。本文介绍了“EALab”,这是一个MATLAB工具箱,旨在简化从商业和独立眼动追踪器收集的眼动数据的提取、多变量分析和分类阶段。该工具箱中实现的处理功能能够评估从包括扫视、注视、眨眼、瞳孔直径和滑音等广泛测量指标中提取的变量。使用EALab不需要任何编程,并且可以通过一个由三个处理模块组成的用户友好型图形用户界面(GUI)进行分析:1)眼动测量指标提取界面,2)变量选择和分析界面,以及3)分类界面。