Towards the automatic detection of social biomarkers in autism spectrum disorder: introducing the simulated interaction task (SIT)
| Autor: | Drimalla, Hanna, Scheffer, Tobias, Landwehr, Niels, Baskow, Irina, Roepke, Stefan, Behnia, Behnoush, Dziobek, Isabel |
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| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: | |
| Zdroj: | NPJ Digital Medicine npj Digital Medicine, Vol 3, Iss 1, Pp 1-10 (2020) |
| DOI: | 10.1038/s41746-020-0227-5 |
| Popis: | **Abstract** Social interaction deficits are evident in many psychiatric conditions and specifically in autism spectrum disorder (ASD), but hard to assess objectively. We present a digital tool to automatically quantify biomarkers of social interaction deficits: the simulated interaction task (SIT), which entails a standardized 7-min simulated dialog via video and the automated analysis of facial expressions, gaze behavior, and voice characteristics. In a study with 37 adults with ASD without intellectual disability and 43 healthy controls, we show the potential of the tool as a diagnostic instrument and for better description of ASD-associated social phenotypes. Using machine-learning tools, we detected individuals with ASD with an accuracy of 73%, sensitivity of 67%, and specificity of 79%, based on their facial expressions and vocal characteristics alone. Especially reduced social smiling and facial mimicry as well as a higher voice fundamental frequency and harmony-to-noise-ratio were characteristic for individuals with ASD. The time-effective and cost-effective computer-based analysis outperformed a majority vote and performed equal to clinical expert ratings. |
| Databáze: | OpenAIRE |
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