Natural-Spontaneous Affective-Cognitive Dataset for Adult Students with and Without Asperger Syndrome

0Citations
Citations of this article
20Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Any viable algorithm to infer affective states of individuals with autism requires natural and reliable data in real time and in an uncontrolled environment. For this purpose, this study provides a new natural-spontaneous affective-cognitive dataset based on facial expressions, eye gaze, and head movements for adult students with and without Asperger syndrome (AS). The data gathering and collecting in a computer-based learning environment is one of the significant areas, which has attracted researchers' attention in affective computing applications. Due to the important impact of emotions on students learning outcome and their performance, the dataset included a range of affective-cognitive states which goes beyond basic emotions. This study reports the methodology that was used in data collection and annotation. Description and comparison of other available datasets were summarized, and also the study presents the results that were concluded in more details. In addition, some challenges were inherent to this study.

Cite

CITATION STYLE

APA

Dawood, A., Turner, S., & Perepa, P. (2019). Natural-Spontaneous Affective-Cognitive Dataset for Adult Students with and Without Asperger Syndrome. IEEE Access, 7, 77990–77999. https://doi.org/10.1109/ACCESS.2019.2921914

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free