一种处理眼动追踪数据的图形用户界面软件。

IF 1.6 Q3 CLINICAL NEUROLOGY
NeuroSci Pub Date : 2025-04-16 DOI:10.3390/neurosci6020035
Daniele Lozzi, Ilaria Di Pompeo, Martina Marcaccio, Matias Ademaj, Simone Migliore, Giuseppe Curcio
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引用次数: 0

摘要

眼动追踪是一种广泛应用于科学研究的工具,它可以获得个体在与视觉刺激相互作用过程中眼球运动的精确和详细数据,从而为视觉感知和相关认知过程提供丰富的信息来源。在这项工作中,提出了一种名为SPEED (labScoc Processing and Extraction of Eye tracking Data)的新软件来处理由瞳孔实验室Neon(瞳孔实验室,柏林,德国)获得的数据。该软件是用Python编写的,可以帮助研究人员在没有任何编码技能的情况下进行特征提取步骤。本研究还提出了一项试点研究,其中包括五名健康受试者,研究MDMT(道德决策任务)期间的动眼肌相关性,并测试参与者表现的可能自主预测因素。在个人困境和非个人困境之间进行选择时,在反应时间和眨眼次数上观察到统计学上显著的差异。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SPEED: A Graphical User Interface Software for Processing Eye Tracking Data.

Eye tracking is a tool that is widely used in scientific research, enabling the acquisition of precise and detailed data on an individual's eye movements during interaction with visual stimuli, thus offering a rich source of information on visual perception and associated cognitive processes. In this work, a new software called SPEED (labScoc Processing and Extraction of Eye tracking Data) is presented to process data acquired by Pupil Lab Neon (Pupil Labs, Berlin, Germany). The software is written in Python which helps researchers with the feature extraction step without any coding skills. This work also presents a pilot study in which five healthy subjects were included in research investigating oculomotor correlates during MDMT (Moral Decision-Making Task) and testing possible autonomic predictors of participants' performance. A statistically significant difference was observed in reaction times and in the number of blinks made during the choice between the conditions of the personal and impersonal dilemma.

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