Digital Phenotyping based on a Mobile App Identifies Distinct and Overlapping Features in Children Diagnosed with Autism versus ADHD
The high prevalence of autism calls for accessible and scalable technology-assisted screening tools. This will aid in early detection allowing timely access to services and supports. SenseToKnow, a mobile digital phenotyping app, showed potential in eliciting autism-related behaviors that can be automatically captured via computer vision analysis (CVA) in toddlers. Here, we present the capability of SenseToKnow in characterizing autism in school age children and showcase the robustness of the CVA features in interpreting distinct and overlapping behaviors with attention-deficit/hyperactive disorder (ADHD).
Authors
- Vikram Aikat
- Guillermo Sapiro (ORCID: https://orcid.org/0000-0001-9190-6964)
- Kimberly L. H. Carpenter (ORCID: https://orcid.org/0000-0002-3838-798X)
- J. Matías Di Martino (ORCID: https://orcid.org/0000-0002-4679-8666)
- Géraldine Dawson (ORCID: https://orcid.org/0000-0003-1410-2764)
- Lauren Franz (ORCID: https://orcid.org/0000-0003-4434-7500)
- Pradeep Raj Krishnappa Babu
- Steven Espinosa (ORCID: https://orcid.org/0000-0001-6831-8312)
- Marina Spanos (ORCID: https://orcid.org/0000-0002-4601-8498)
- Naomi Ornstein Davis (ORCID: https://orcid.org/0000-0003-0858-7152)
Institutions
- Duke University (US)
- Office of the National Coordinator for Health Information Technology (US)
- Universidad Católica del Uruguay (UY)
- Center for Autism and Related Disorders (US)
Publication Details
- Published
- 2024-10-11
- DOI
- https://doi.org/10.1145/3672539.3686323
- Citations
- 1
- Primary Topic
- Autism Spectrum Disorder Research
- Type
- article
- Field-Weighted Citation Impact
- 0.34