TY - GEN
T1 - Assessing the Social Skills of Children with Autism Spectrum Disorder via Language-Image Pre-training Models
AU - Liu, Wenxing
AU - Cheng, Ming
AU - Pan, Yueran
AU - Yuan, Lynn
AU - Hu, Suxiu
AU - Li, Ming
AU - Zeng, Songtian
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.
PY - 2024
Y1 - 2024
N2 - Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that has gained global attention due to its prevalence. Clinical assessment measures rely heavily on manual scoring conducted by specialized physicians. However, this approach exhibits subjectivity and challenges in regions without sufficient medical resources. This study presents paradigms designed to automatically evaluate various aspects of social skills in children with ASD, utilizing our multiview and multimodal behavior system. Moreover, we propose a new pipeline to predict autism-related social skill scores using the language-image pre-training model. Our multimodal behavioral database comprises 12 subjects (511 videos with labeled social skill scores). Finally, we achieve 81.46% accuracy on the paradigm success prediction task and 69.23% accuracy on the social skill ability scoring task. The results demonstrate that the language-image pre-training model can effectively introduce domain knowledge into video assessment tasks.
AB - Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that has gained global attention due to its prevalence. Clinical assessment measures rely heavily on manual scoring conducted by specialized physicians. However, this approach exhibits subjectivity and challenges in regions without sufficient medical resources. This study presents paradigms designed to automatically evaluate various aspects of social skills in children with ASD, utilizing our multiview and multimodal behavior system. Moreover, we propose a new pipeline to predict autism-related social skill scores using the language-image pre-training model. Our multimodal behavioral database comprises 12 subjects (511 videos with labeled social skill scores). Finally, we achieve 81.46% accuracy on the paradigm success prediction task and 69.23% accuracy on the social skill ability scoring task. The results demonstrate that the language-image pre-training model can effectively introduce domain knowledge into video assessment tasks.
KW - Autism Spectrum Disorder
KW - Behavior
KW - Language-Image Pre-training Models
KW - Social Skills Assessment
UR - https://www.scopus.com/pages/publications/85181765346
UR - https://www.scopus.com/pages/publications/85181765346#tab=citedBy
U2 - 10.1007/978-981-99-8558-6_22
DO - 10.1007/978-981-99-8558-6_22
M3 - Conference contribution
AN - SCOPUS:85181765346
SN - 9789819985579
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 260
EP - 271
BT - Pattern Recognition and Computer Vision - 6th Chinese Conference, PRCV 2023, Proceedings
A2 - Liu, Qingshan
A2 - Wang, Hanzi
A2 - Ji, Rongrong
A2 - Ma, Zhanyu
A2 - Zheng, Weishi
A2 - Zha, Hongbin
A2 - Chen, Xilin
A2 - Wang, Liang
PB - Springer Science and Business Media Deutschland GmbH
T2 - 6th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2023
Y2 - 13 October 2023 through 15 October 2023
ER -