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Using Wearable Sensor Technology to Measure Motion Complexity in Infants at High Familial Risk for Autism Spectrum
Rujuta B Wilson1, Sitaram Vangala2, David Elashoff2
1Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, 760 Westwood Plaza, Los Angeles, CA 90095, USA.
Insights
Infants at high familial risk for autism spectrum disorder (ASD) show less complex motion patterns. This motion complexity measure may help identify infants who will later be diagnosed with ASD.
Area of Science:
- Developmental neuroscience
- Autism spectrum disorder research
- Infant motor development
Background:
- Motor dysfunction is an early indicator in infants at high familial risk for autism spectrum disorder (ASD).
- Previous studies show inconsistent findings on the nature and predictability of infant motor dysfunction for later ASD diagnosis.
- Standardized motor assessments may miss subtle, early motor impairments; quantitative measures offer objective evaluation.
Purpose of the Study:
- To longitudinally evaluate full-day motor activity in high-risk (HR) infants using wearable sensors.
- To develop and validate a novel measure of "motion complexity" for infant motor development.
- To examine the relationship between motion complexity and later developmental outcomes, including ASD diagnosis.
Main Methods:
- Utilized Opal wearable sensors for continuous, full-day motor activity tracking in HR infants.
- Developed a quantitative "motion complexity" metric, hypothesizing that reduced complexity may indicate repetitive motor behaviors.
- Examined the correlation between motion complexity and subsequent ASD diagnosis, cognitive ability, and adaptive skills in a pilot cohort.
Main Results:
- HR infants later diagnosed with ASD exhibited significantly lower motion complexity compared to those without an ASD diagnosis.
- Motion complexity demonstrated a stronger correlation with ASD outcome than with cognitive ability or adaptive skills.
- This suggests motion complexity is a sensitive marker for atypical motor development in infants at risk for ASD.
Conclusions:
- Objective motor development measures, like motion complexity, are crucial for identifying sensitive and specific markers of ASD risk in infancy.
- Motion complexity shows promise as a tool for tracking early motor development and differentiating HR infants who will develop ASD.
- This quantitative approach may improve early identification and intervention for autism spectrum disorder.
Background:
Motor dysfunction has been reported as one of the first signs of atypical development in infants at high familial risk for autism spectrum disorder (ASD) (HR infants). However, studies have shown inconsistent results regarding the nature of motor dysfunction and whether it can be predictive of later ASD diagnosis. This is likely because current standardized motor assessments may not identify subtle and specific motor impairments that precede clinically observable motor dysfunction. Quantitative measures of motor development may address these limitations by providing objective evaluation of subtle motor differences in infancy.
Methods:
We used Opal wearable sensors to longitudinally evaluate full day motor activity in HR infants, and develop a measure of motion complexity. We focus on complexity of motion because optimal motion complexity is crucial to normal motor development and less complex behaviors might represent repetitive motor behaviors, a core diagnostic symptom of ASD. As proof of concept, the relationship of the motion complexity measure to developmental outcomes was examined in a small set of HR infants.
Results:
HR infants with a later diagnosis of ASD show lower motion complexity compared to those that do not. There is a stronger correlation between motion complexity and ASD outcome compared to outcomes of cognitive ability and adaptive skills.
Conclusions:
Objective measures of motor development are needed to identify characteristics of atypical infant motor function that are sensitive and specific markers of later ASD risk. Motion complexity could be used to track early infant motor development and to discriminate HR infants that go on to develop ASD.
