Paper Info
Title
Natural-Spontaneous Affective-Cognitive Dataset For Adult Students With And Without Asperger Syndrome
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.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2921914
IEEE ACCESS
Keywords
Field
DocType
Emotional dataset, autism, Asperger syndrome, spontaneous, natural, facial expressions, affective computing, affective-cognitive states
Autism,Computer science,Asperger syndrome,Cognitive psychology,Computer network,Facial expression,Affective computing,Cognition,Affect (psychology)
Journal
Volume
ISSN
Citations 
7
2169-3536
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Amina Dawood100.68
Scott Turner263.96
Prithvi Perepa300.34