婴儿期早期的自我触摸和其他自发行为模式

Jason Khoury, S. T. Popescu, Filipe Gama, Valentin Marcel, M. Hoffmann
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引用次数: 2

摘要

孩子不是出生在白板上的。然而,在出生后的头几个月里,通过身体运动与环境互动对于建立模型或表征至关重要,而模型或表征是接下来一切的基础。我们提出纵向数据的自发行为的三个婴儿之间观察大约8和25周龄仰卧位。为了研究婴儿的行为模式和发育进程,我们将视频录像的手动评分与动作数据的自动提取相结合,包括:(i)自我触摸在身体上的空间分布,(ii)手部运动的空间模式和规律,(iii)中线交叉,(iv)优先使用一只手臂,以及(v)指示目标定向的动态动作模式。从这个试点数据集中观察到的模式,我们可以推测第一身体和周围个人空间表征的发展。最近,计算机视觉社区已经提供了几种从视频中提取3D运动学的方法。我们将其中一种方法应用于婴儿视频,并提供了关于其可能性和局限性的指南——这是对婴儿视频自动化分析的方法论贡献。在未来,我们计划使用我们从录音中提取的模式作为婴儿身体表征学习的具身计算模型的输入。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Self-touch and other spontaneous behavior patterns in early infancy
Children are not born tabula rasa. However, interacting with the environment through their body movements in the first months after birth is critical to building the models or representations that are the foundation for everything that follows. We present longitudinal data on spontaneous behavior of three infants observed between about 8 and 25 weeks of age in supine position. We combined manual scoring of video recordings with an automatic extraction of motion data in order to study infants’ behavioral patterns and developmental progression such as: (i) spatial distribution of self-touches on the body, (ii) spatial patterns and regularities of hand movements, (iii) midline crossing, (iv) preferential use of one arm, and (v) dynamic patterns of movements indicative of goal-directedness. From the patterns observed in this pilot data set, we can speculate on the development of first body and peripersonal space representations. Several methods of extracting 3D kinematics from videos have recently been made available by the computer vision community. We applied one of these methods on infant videos and provide guidelines on its possibilities and limitations—a methodological contribution to automating the analysis of infant videos. In the future, we plan to use the patterns we extracted from the recordings as inputs to embodied computational models of learning of body representations in infancy.
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