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Autism Spectrum Disorder Eye-Gaze Data
Mental Health & Wellness
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About
This dataset is designed to support research into Autism Spectrum Disorder (ASD), focusing on eye-tracking methodologies. Eye-tracking is a widely used technique in autism diagnosis, with abnormalities in eye gaze being a recognised indicator of autism. The dataset is intended to facilitate the development of valuable applications and the discovery of novel insights within this field. A key application is its potential use with Machine Learning to build diagnostic models for the early detection of autism.
Columns
The primary metadata file,
Participants.csv, includes the following key columns:- ParticipantID: A unique identifier assigned to each participant in the study.
- Gender: Indicates the participant's gender, either 'M' (Male) or 'F' (Female). In the sample data, 64% are male and 36% are female.
- Age: Represents the age of the participants, ranging from 2.7 to 12.9 years, with a mean age of 7.88 years.
- Class: Categorises participants as either 'TD' (Typically Developing) or 'ASD' (Autism Spectrum Disorder). The sample indicates 51% are TD and 49% are ASD.
- CARS Score: Refers to the Childhood Autism Rating Scale score. It includes numerical values and 'NA' for participants where the score is not applicable or not provided.
Distribution
The dataset is distributed across 25 separate CSV-formatted files, with each file representing the output of a single eye-tracking experiment. Typically, a single experiment involves multiple participants. Participant IDs are clearly provided within each record, allowing for identification of a participant's class (Typically Developing or ASD). Additionally, a set of metadata files is included, with
Participants.csv detailing the main characteristics of the study participants. The Participants.csv file contains 59 valid records for the described columns.Usage
This dataset is ideal for:
- Developing useful applications related to autism diagnosis and support.
- Discovering interesting insights into eye-tracking patterns and their correlation with autism.
- Building Machine Learning models aimed at diagnosing autism at an early developmental stage.
Coverage
The dataset's scope is defined by its participant characteristics rather than specific geographical or extensive time range details. It includes demographic information such as gender and age (2.7 to 12.9 years). Crucially, it covers both Typically Developing (TD) and Autism Spectrum Disorder (ASD) participant groups, with a nearly equal distribution (51% TD, 49% ASD). The data relates to research conducted around 2022, and the dataset is not expected to be updated.
License
CC BY-SA 4.0
Who Can Use It
This dataset is intended for a broad range of users interested in autism research and related technological applications, including:
- Academic researchers studying autism spectrum disorder and eye-tracking methodologies.
- Data scientists and Machine Learning engineers developing diagnostic tools or predictive models.
- Healthcare professionals interested in data-driven insights for early intervention strategies.
Dataset Name Suggestions
- Eye Tracking Autism Dataset for Research
- Autism Spectrum Disorder Eye-Gaze Data
- Paediatric Eye-Tracking for ASD Diagnosis
- Autism Eye-Tracking Study Data
Attributes
Original Data Source : Autism Spectrum Disorder Eye-Gaze Data
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