Early detection of autism using digital behavioral phenotyping.

Early detection of autism, a neurodevelopmental condition associated with challenges in social communication, ensures timely access to intervention. Autism screening questionnaires have been shown to have lower accuracy when used in real-world settings, such as primary care, as compared to research studies, particularly for children of color and girls. Here we report findings from a multiclinic, prospective study assessing the accuracy of an autism screening digital application (app) administered during a pediatric well-child visit to 475 (17-36 months old) children (269 boys and 206 girls), of which 49 were diagnosed with autism and 98 were diagnosed with developmental delay without autism.

Exploring Complexity of Facial Dynamics in Autism Spectrum Disorder.

Atypical facial expression is one of the early symptoms of autism spectrum disorder (ASD) characterized by reduced regularity and lack of coordination of facial movements. Automatic quantification of these behaviors can offer novel biomarkers for screening, diagnosis, and treatment monitoring of ASD. In this work, 40 toddlers with ASD and 396 typically developing toddlers were shown developmentally-appropriate and engaging movies presented on a smart tablet during a well-child pediatric visit.

Blink rate and facial orientation reveal distinctive patterns of attentional engagement in autistic toddlers: a digital phenotyping approach.

Differences in social attention are well-documented in autistic individuals, representing one of the earliest signs of autism. Spontaneous blink rate has been used to index attentional engagement, with lower blink rates reflecting increased engagement. We evaluated novel methods using computer vision analysis (CVA) for automatically quantifying patterns of attentional engagement in young autistic children, based on facial orientation and blink rate, which were captured via mobile devices.

A tablet-based game for the assessment of visual motor skills in autistic children.

Increasing evidence suggests that early motor impairments are a common feature of autism. Thus, scalable, quantitative methods for measuring motor behavior in young autistic children are needed. This work presents an engaging and scalable assessment of visual-motor abilities based on a bubble-popping game administered on a tablet.

Complexity analysis of head movements in autistic toddlers.

Background: Early differences in sensorimotor functioning have been documented in young autistic children and infants who are later diagnosed with autism. Previous research has demonstrated that autistic toddlers exhibit more frequent head movement when viewing dynamic audiovisual stimuli, compared to neurotypical toddlers. To further explore this behavioral characteristic, in this study, computer vision (CV) analysis was used to measure several aspects of head movement dynamics of autistic and neurotypical toddlers while they watched a set of brief movies with social and nonsocial content presented on a tablet.

Computational Methods to Measure Patterns of Gaze in Toddlers With Autism Spectrum Disorder.

Importance: Atypical eye gaze is an early-emerging symptom of autism spectrum disorder (ASD) and holds promise for autism screening. Current eye-tracking methods are expensive and require special equipment and calibration. There is a need for scalable, feasible methods for measuring eye gaze.

A scalable computational approach to assessing response to name in toddlers with autism.

Background: This 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.

Methods: During 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.

Computer Vision Analysis for Quantification of Autism Risk Behaviors.

Observational behavior analysis plays a key role for the discovery and evaluation of risk markers for many neurodevelopmental disorders. Research on autism spectrum disorder (ASD) suggests that behavioral risk markers can be observed at 12 months of age or earlier, with diagnosis possible at 18 months. To date, these studies and evaluations involving observational analysis tend to rely heavily on clinical practitioners and specialists who have undergone intensive training to be able to reliably administer carefully designed behavioural-eliciting tasks, code the resulting behaviors, and interpret such behaviors.

Digital Behavioral Phenotyping Detects Atypical Pattern of Facial Expression in Toddlers with Autism.

Commonly used screening tools for autism spectrum disorder (ASD) generally rely on subjective caregiver questionnaires. While behavioral observation is more objective, it is also expensive, time-consuming, and requires significant expertise to perform. As such, there remains a critical need to develop feasible, scalable, and reliable tools that can characterize ASD risk behaviors.

Impact of a digital Modified Checklist for Autism in Toddlers-Revised on likelihood and age of autism diagnosis and referral for developmental evaluation.

This was a project in primary care for young children (1-2 years old). We tested a parent questionnaire on a tablet. This tablet questionnaire asked questions to see whether the child may have autism.

Author Correction: Atypical postural control can be detected via computer vision analysis in toddlers with autism spectrum disorder.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Automatic emotion and attention analysis of young children at home: a ResearchKit autism feasibility study.

Current tools for objectively measuring young children's observed behaviors are expensive, time-consuming, and require extensive training and professional administration. The lack of scalable, reliable, and validated tools impacts access to evidence-based knowledge and limits our capacity to collect population-level data in non-clinical settings. To address this gap, we developed mobile technology to collect videos of young children while they watched movies designed to elicit autism-related behaviors and then used automatic behavioral coding of these videos to quantify children's emotions and behaviors.

Atypical postural control can be detected via computer vision analysis in toddlers with autism spectrum disorder.

Evidence suggests that differences in motor function are an early feature of autism spectrum disorder (ASD). One aspect of motor ability that develops during childhood is postural control, reflected in the ability to maintain a steady head and body position without excessive sway. Observational studies have documented differences in postural control in older children with ASD.

Computer vision analysis captures atypical attention in toddlers with autism.

To demonstrate the capability of computer vision analysis to detect atypical orienting and attention behaviors in toddlers with autism spectrum disorder. One hundered and four toddlers of 16-31 months old (mean = 22) participated in this study. Twenty-two of the toddlers had autism spectrum disorder and 82 had typical development or developmental delay.

Use of a Digital Modified Checklist for Autism in Toddlers - Revised with Follow-up to Improve Quality of Screening for Autism.

Objectives: To assess changes in quality of care for children at risk for autism spectrum disorders (ASD) due to process improvement and implementation of a digital screening form.

Study Design: The process of screening for ASD was studied in an academic primary care pediatrics clinic before and after implementation of a digital version of the Modified Checklist for Autism in Toddlers - Revised with Follow-up with automated risk assessment. Quality metrics included accuracy of documentation of screening results and appropriate action for positive screens (secondary screening or referral).