Machine learning accurately classifies age of toddlers based on eye tracking
Machine learning accurately classifies age of toddlers based on eye tracking
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DOI：
10.1038/s41598-019-42764-z
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发表时间：
2019-04-18
影响因子：
4.6
通讯作者：
Elison, Jed T.
中科院分区：
文献类型：
--
作者：
Dalrymple, Kirsten A.;Jiang, Ming;Elison, Jed T.
人们如何从复杂的场景中提取视觉信息提供了关于认知过程的重要信息。使用自然主义而不是高度控制的实验刺激进行的眼动跟踪研究表明，观看行为的可变性是由自下而上的图像属性(如强度、颜色和方向)、自上而下的因素(如任务指令和语义信息)以及遗传、认知功能和社会功能的个体差异决定的。这些差异通常是通过实验者或其他人类观察者选择的感兴趣区域来揭示的。相反，我们采用了数据驱动的方法，使用机器学习(支持向量机和深度学习)来阐明凝视模式中与年龄相关的变异性的影响因素。这些模型按年龄对婴儿进行分类，准确率很高，并确定了区分年龄组的有意义的特征。我们的结果表明，机器学习是一种有效的工具，可以理解看起来如何随着年龄的变化而变化，为幼儿如何分配注意力以及如何随着发展而变化提供了洞察。这种检测幼儿探索性凝视行为差异的敏感性突出了机器学习在表征各种发展能力方面的作用。
How people extract visual information from complex scenes provides important information about cognitive processes. Eye tracking studies that have used naturalistic, rather than highly controlled experimental stimuli, reveal that variability in looking behavior is determined by bottom-up image properties such as intensity, color, and orientation, top-down factors such as task instructions and semantic information, and individual differences in genetics, cognitive function and social functioning. These differences are often revealed using areas of interest that are chosen by the experimenter or other human observers. In contrast, we adopted a data-driven approach by using machine learning (Support Vector Machine (SVM) and Deep Learning (DL)) to elucidate factors that contribute to age-related variability in gaze patterns. These models classified the infants by age with a high degree of accuracy, and identified meaningful features distinguishing the age groups. Our results demonstrate that machine learning is an effective tool for understanding how looking patterns vary according to age, providing insight into how toddlers allocate attention and how that changes with development. This sensitivity for detecting differences in exploratory gaze behavior in toddlers highlights the utility of machine learning for characterizing a variety of developmental capacities.