ArticleJournal of child psychology and psychiatry, and allied disciplines2021
A scalable computational approach to assessing response to name in toddlers with autism.
Article in Journal of child psychology and psychiatry, and allied disciplines, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed, 35 citations in OpenAlex.
- Early Detection Methods for Autism Spectrum Disorder: From Clinical Screening to Multimodal AI.Diagnostics (Basel, Switzerland) · 2026Review
- Use of computer vision analysis for labeling inattention periods in EEG recordings with visual stimuli.Scientific reports · 2025Article
- Autism Digital Phenotyping in Preschool- and School-Age Children.Autism research : official journal of the International Society for Autism Research · 2025Article
- Detecting Autism from Head Movements using Kinesics.Proceedings of the ... ACM International Conference on Multimodal Interaction. ICMI (Conference) · 2024Article
- Autism Spectrum Disorder in Children: Early Signs and Therapeutic Interventions.Children (Basel, Switzerland) · 2024Review
- Article
- Computer Vision Analysis of Caregiver-Child Interactions in Children with Neurodevelopmental Disorders: A Preliminary Report.Journal of autism and developmental disorders · 2024Article
- Autism Caregiver Coaching in Africa (ACACIA): Protocol for a type 1-hybrid effectiveness-implementation trial.PloS one · 2024Article
- The ChAMP App: A Scalable mHealth Technology for Detecting Digital Phenotypes of Early Childhood Mental Health.medRxiv : the preprint server for health sciences · 2023Article
- The ChAMP App: A Scalable mHealth Technology for Detecting Digital Phenotypes of Early Childhood Mental Health.IEEE journal of biomedical and health informatics · 2023Article
- Early detection of autism using digital behavioral phenotyping.Nature medicine · 2023Article
- Autism Caregiver Coaching in Africa (ACACIA): Protocol for a type 1-hybrid effectiveness-implementation trial.medRxiv : the preprint server for health sciences · 2023Article
- Relationship between quantitative digital behavioral features and clinical profiles in young autistic children.Autism research : official journal of the International Society for Autism Research · 2023Article
- Blink rate and facial orientation reveal distinctive patterns of attentional engagement in autistic toddlers: a digital phenotyping approach.Scientific reports · 2023Article
- Prediction of autism in infants: progress and challenges.The Lancet. Neurology · 2023Review
- A tablet-based game for the assessment of visual motor skills in autistic children.NPJ digital medicine · 2023Article
- A multimodal machine learning system in early screening for toddlers with autism spectrum disorders based on the response to name.Frontiers in psychiatry · 2023Article
- Complexity analysis of head movements in autistic toddlers.Journal of child psychology and psychiatry, and allied disciplines · 2023Article
- A systematic review of telehealth screening, assessment, and diagnosis of autism spectrum disorder.Child and adolescent psychiatry and mental health · 2022Review
- Identifying Autism with Head Movement Features by Implementing Machine Learning Algorithms.Journal of autism and developmental disorders · 2022Article
Corrections and comments
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Authors and funding
22 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundThis study is part of a larger research program focused on developing objective, scalable tools for digital behavioral phenotyping. We evaluated whether a digital app delivered on a smartphone or tablet using computer vision analysis (CVA) can elicit and accurately measure one of the most common early autism symptoms, namely failure to respond to a name call.
methodsDuring a pediatric primary care well-child visit, 910 toddlers, 17-37 months old, were administered an app on an iPhone or iPad consisting of brief movies during which the child's name was called three times by an examiner standing behind them. Thirty-seven toddlers were subsequently diagnosed with autism spectrum disorder (ASD). Name calls and children's behavior were recorded by the camera embedded in the device, and children's head turns were coded by both CVA and a human.
resultsCVA coding of response to name was found to be comparable to human coding. Based on CVA, children with ASD responded to their name significantly less frequently than children without ASD. CVA also revealed that children with ASD who did orient to their name exhibited a longer latency before turning their head. Combining information about both the frequency and the delay in response to name improved the ability to distinguish toddlers with and without ASD.
conclusionsA digital app delivered on an iPhone or iPad in real-world settings using computer vision analysis to quantify behavior can reliably detect a key early autism symptom-failure to respond to name. Moreover, the higher resolution offered by CVA identified a delay in head turn in toddlers with ASD who did respond to their name. Digital phenotyping is a promising methodology for early assessment of ASD symptoms.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.