Eye-Tracking Dataset to Support the Research on Autism Spectrum Disorder

<strong>Abstract:</strong> This study aims to publish an eye-tracking dataset developed for the purpose of autism diagnosis. Eye-tracking methods are used intensively in that context, whereas abnormalities of the eye gaze are largely recognised as the hallmark of autism. As such, it is believed that the dataset can allow for developing useful applications or discovering interesting insights. As well, Machine Learning is a potential application for developing diagnostic models that can help detect autism at an early stage of development. <br> <strong>Dataset Description:</strong> The dataset is distributed over 25 CSV-formatted files. Each file represents the output of an eye-tracking experiment. However, a single experiment usually included multiple participants. The participant ID is clearly provided at each record at the ‘Participant’ column, which can be used to identify the class of participant (i.e., Typically Developing or ASD). Furthermore, a set of metadata files is included. The main metadata file, Participants.csv, is used to describe the key characteristics of participants (e.g. gender, age, CARS). Every participant was also assigned a unique ID. <br> <strong>Dataset Citation:</strong> Cilia, F., Carette, R., Elbattah, M., Guérin, J., &amp; Dequen, G. (2022). Eye-Tracking Dataset to Support the Research on Autism Spectrum Disorder. In Proceedings of the IJCAI–ECAI Workshop on Scarce Data in Artificial Intelligence for Healthcare (SDAIH). <br>

**摘要：** 本研究旨在发布一款专为自闭症诊断开发的眼动追踪（eye-tracking）数据集。眼动追踪方法在该研究领域中应用广泛，而眼动异常已被广泛认定为自闭症的标志性特征。据此认为，本数据集可用于开发实用应用程序或发掘有价值的研究见解。此外，机器学习（Machine Learning）是开发诊断模型的潜在技术路径，此类模型可助力在疾病发展早期阶段检测出自闭症。
**数据集说明：** 本数据集包含25个CSV格式文件，每个文件对应一次眼动追踪实验的输出结果。单次实验通常会纳入多名受试者。每条记录的「Participant」列中均清晰标注了受试者编号，可通过该编号识别受试者类别（即典型发育人群或自闭症谱系障碍（Autism Spectrum Disorder, ASD）患者）。此外，数据集附带一组元数据文件，其中核心元数据文件为Participants.csv，用于描述受试者的关键特征（如性别、年龄、儿童自闭症评定量表（CARS）），且每位受试者均被分配了唯一编号。
**数据集引用：** Cilia, F., Carette, R., Elbattah, M., Guérin, J. & Dequen, G. (2022). 支持自闭症谱系障碍研究的眼动追踪数据集。发表于《IJCAI–ECAI医疗人工智能稀缺数据研讨会（SDAIH）论文集》。