Digital Phenotyping based on a Mobile App Identifies Distinct and Overlapping Features in Children Diagnosed with Autism versus ADHD

Vikram Aikat; Pradeep Raj Krishnappa Babu; Kimberly L.H. Carpenter; J. Matias Di Martino; Steven Espinosa; Naomi Davis; Lauren Franz; Marina Spanos; Geraldine Dawson; Guillermo Sapiro

doi:10.1145/3672539.3686323

Digital Phenotyping based on a Mobile App Identifies Distinct and Overlapping Features in Children Diagnosed with Autism versus ADHD

Vikram Aikat, Pradeep Raj Krishnappa Babu, Kimberly L.H. Carpenter, J. Matias Di Martino, Steven Espinosa, Naomi Davis, Lauren Franz, Marina Spanos, Geraldine Dawson, Guillermo Sapiro

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

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).

Original language	English (US)
Title of host publication	UIST Adjunct 2024 - Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology
Publisher	Association for Computing Machinery, Inc
ISBN (Electronic)	9798400707186
DOIs	https://doi.org/10.1145/3672539.3686323
State	Published - Oct 13 2024
Externally published	Yes
Event	37th Annual ACM Symposium on User Interface Software and Technology, UIST Adjunct 2024 - Pittsburgh, United States Duration: Oct 13 2024 → Oct 16 2024

Publication series

Name	UIST Adjunct 2024 - Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology

Conference

Conference	37th Annual ACM Symposium on User Interface Software and Technology, UIST Adjunct 2024
Country/Territory	United States
City	Pittsburgh
Period	10/13/24 → 10/16/24

All Science Journal Classification (ASJC) codes

Human-Computer Interaction
Software

Keywords

ADHD
Autism
Computer Vision
Digital Phenotyping

Access to Document

10.1145/3672539.3686323

Cite this

Aikat, V., Krishnappa Babu, P. R., Carpenter, K. L. H., Di Martino, J. M., Espinosa, S., Davis, N., Franz, L., Spanos, M., Dawson, G., & Sapiro, G. (2024). Digital Phenotyping based on a Mobile App Identifies Distinct and Overlapping Features in Children Diagnosed with Autism versus ADHD. In UIST Adjunct 2024 - Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology Article 111 (UIST Adjunct 2024 - Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology). Association for Computing Machinery, Inc. https://doi.org/10.1145/3672539.3686323

Aikat, Vikram ; Krishnappa Babu, Pradeep Raj ; Carpenter, Kimberly L.H. et al. / Digital Phenotyping based on a Mobile App Identifies Distinct and Overlapping Features in Children Diagnosed with Autism versus ADHD. UIST Adjunct 2024 - Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology. Association for Computing Machinery, Inc, 2024. (UIST Adjunct 2024 - Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology).

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abstract = "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).",

keywords = "ADHD, Autism, Computer Vision, Digital Phenotyping",

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doi = "10.1145/3672539.3686323",

language = "English (US)",

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Aikat, V, Krishnappa Babu, PR, Carpenter, KLH, Di Martino, JM, Espinosa, S, Davis, N, Franz, L, Spanos, M, Dawson, G & Sapiro, G 2024, Digital Phenotyping based on a Mobile App Identifies Distinct and Overlapping Features in Children Diagnosed with Autism versus ADHD. in UIST Adjunct 2024 - Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology., 111, UIST Adjunct 2024 - Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology, Association for Computing Machinery, Inc, 37th Annual ACM Symposium on User Interface Software and Technology, UIST Adjunct 2024, Pittsburgh, United States, 10/13/24. https://doi.org/10.1145/3672539.3686323

Digital Phenotyping based on a Mobile App Identifies Distinct and Overlapping Features in Children Diagnosed with Autism versus ADHD. / Aikat, Vikram; Krishnappa Babu, Pradeep Raj; Carpenter, Kimberly L.H. et al.
UIST Adjunct 2024 - Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology. Association for Computing Machinery, Inc, 2024. 111 (UIST Adjunct 2024 - Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Krishnappa Babu, Pradeep Raj

AU - Carpenter, Kimberly L.H.

AU - Di Martino, J. Matias

AU - Espinosa, Steven

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AU - Spanos, Marina

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AB - 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).

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Aikat V, Krishnappa Babu PR, Carpenter KLH, Di Martino JM, Espinosa S, Davis N et al. Digital Phenotyping based on a Mobile App Identifies Distinct and Overlapping Features in Children Diagnosed with Autism versus ADHD. In UIST Adjunct 2024 - Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology. Association for Computing Machinery, Inc. 2024. 111. (UIST Adjunct 2024 - Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology). doi: 10.1145/3672539.3686323

Digital Phenotyping based on a Mobile App Identifies Distinct and Overlapping Features in Children Diagnosed with Autism versus ADHD

Abstract

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All Science Journal Classification (ASJC) codes

Keywords

Access to Document

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