Video-based Analysis Reveals Atypical Social Gaze in People with Autism Spectrum Disorder
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arXiv
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| Auteurs principaux: | , , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866916377245253632 |
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| author | Yu, Xiangxu Ruan, Mindi Hu, Chuanbo Li, Wenqi Paul, Lynn K. Li, Xin Wang, Shuo |
| author_facet | Yu, Xiangxu Ruan, Mindi Hu, Chuanbo Li, Wenqi Paul, Lynn K. Li, Xin Wang, Shuo |
| contents | In this study, we present a quantitative and comprehensive analysis of social gaze in people with autism spectrum disorder (ASD). Diverging from traditional first-person camera perspectives based on eye-tracking technologies, this study utilizes a third-person perspective database from the Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) interview videos, encompassing ASD participants and neurotypical individuals as a reference group. Employing computational models, we extracted and processed gaze-related features from the videos of both participants and examiners. The experimental samples were divided into three groups based on the presence of social gaze abnormalities and ASD diagnosis. This study quantitatively analyzed four gaze features: gaze engagement, gaze variance, gaze density map, and gaze diversion frequency. Furthermore, we developed a classifier trained on these features to identify gaze abnormalities in ASD participants. Together, we demonstrated the effectiveness of analyzing social gaze in people with ASD in naturalistic settings, showcasing the potential of third-person video perspectives in enhancing ASD diagnosis through gaze analysis. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_00664 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Video-based Analysis Reveals Atypical Social Gaze in People with Autism Spectrum Disorder Yu, Xiangxu Ruan, Mindi Hu, Chuanbo Li, Wenqi Paul, Lynn K. Li, Xin Wang, Shuo Neurons and Cognition Machine Learning In this study, we present a quantitative and comprehensive analysis of social gaze in people with autism spectrum disorder (ASD). Diverging from traditional first-person camera perspectives based on eye-tracking technologies, this study utilizes a third-person perspective database from the Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2) interview videos, encompassing ASD participants and neurotypical individuals as a reference group. Employing computational models, we extracted and processed gaze-related features from the videos of both participants and examiners. The experimental samples were divided into three groups based on the presence of social gaze abnormalities and ASD diagnosis. This study quantitatively analyzed four gaze features: gaze engagement, gaze variance, gaze density map, and gaze diversion frequency. Furthermore, we developed a classifier trained on these features to identify gaze abnormalities in ASD participants. Together, we demonstrated the effectiveness of analyzing social gaze in people with ASD in naturalistic settings, showcasing the potential of third-person video perspectives in enhancing ASD diagnosis through gaze analysis. |
| title | Video-based Analysis Reveals Atypical Social Gaze in People with Autism Spectrum Disorder |
| topic | Neurons and Cognition Machine Learning |
| url | https://arxiv.org/abs/2409.00664 |