ArticleAutism research : official journal of the International Society for Autism Research2024
Objective measurement of movement variability using wearable sensors predicts ASD outcomes in infants at high likelihood for ASD and ADHD.
Article in Autism research : official journal of the International Society for Autism Research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Movement-Related Differences Between Infants with High and Low Likelihood of Autism: A Longitudinal Study Using Markerless Motion Tracking.Sensors (Basel, Switzerland) · 2026Article
- A Novel Workflow to Estimate Limb Orientation from Wearable Sensors to Monitor Infant Motor Development.Sensors (Basel, Switzerland) · 2026Article
- Automatic pose estimation in newborn infants: Lessons from the Baby Grow study.Behavior research methods · 2026Article
- Video and Wearable Sensor Technologies for Early Detection of Cerebral Palsy in Infants: A Scoping Review.Journal of clinical medicine · 2026Review
- Early motor trajectories in infants at increased genetic likelihood for autism.Frontiers in developmental psychology · 2026Article
- Artificial-intelligence-based developmental screening for pre-school children (ages 3-6): a scoping review of deployed tools, clinical validity, equity, and implementation in guidance-center settings.Frontiers in psychology · 2026Review
- ViT-BiLSTM Multimodal Learning for Paediatric ADHD Recognition: Integrating Wearable Sensor Data with Clinical Profiles.Sensors (Basel, Switzerland) · 2025Article
- Survey of Child Neurologists Highlights a Missed Opportunity for Identifying and Treating Motor Impairments in Autism.Pediatric neurology · 2025Article
- Wearable sensors in paediatric neurology.Developmental medicine and child neurology · 2025Review
- Visual feedback and motor memory contributions to sustained motor control deficits in autism spectrum disorder across childhood and into adulthood.Journal of neurodevelopmental disorders · 2025Article
- Physiological parameters to support attention deficit hyperactivity disorder diagnosis in children: a multiparametric approach.Frontiers in psychiatry · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Early motor delays and differences are common among children with autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD). Yet, little work has shown whether there are early atypical motor signs that differentiate these groups. Quantitative measures of movement variability hold promise for improving the identification of subtle and specific differences in motor function among infants and toddlers at high likelihood for ASD and ADHD. To this end, we created a novel quantitative measure of movement variability (movement curvature) and conducted a preliminary investigation as to whether this measure improves outcome predictions. We used a wearable triaxial accelerometer to evaluate continuous motion-based activity in infants at high and low likelihood for ASD and ADHD at 12, 18, 24, and 36 months of age. At 36 months, participants were categorized into three outcome groups: ASD (n = 19), ADHD concerns (n = 17), and a comparison group (n = 82). We examined group differences in movement curvature and whether movement curvature is predictive of a later ASD or ADHD concerns classification. We found that movement curvature was significantly lower in infants with later ASD diagnosis at 18, 24, and 36 months of age compared to infants with either ADHD concerns or those in the comparison group. Movement curvature was also a significant predictor of ASD at 18, 24, and 36 months (AUC 0.66-0.71; p = 0.005-0.039) and when adjusting for high ASD likelihood at 18 and 24 months (AUC 0.90, p = 0.05-0.019). These results indicate that lower movement curvature may be a feature of early motor differences in infants with later ASD diagnosis as early as 18 months of age.
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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 Socratic graph.