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Using Wearable Sensor Technology to Measure Motion Complexity in Infants at High Familial Risk for Autism Spectrum Disorder
by
Smith, Beth A.
, Elashoff, David
, Safari, Tabitha
, Wilson, Rujuta B.
, Vangala, Sitaram
in
Age
/ Autism
/ autism spectrum disorder
/ Autism Spectrum Disorder - diagnosis
/ Autism Spectrum Disorder - genetics
/ Babies
/ Cognition
/ Early childhood education
/ Genetic Predisposition to Disease
/ Humans
/ Infant
/ Longitudinal studies
/ Motor ability
/ motor development
/ Preschool children
/ quantitative measures
/ Sensors
/ Standard scores
/ Technology
/ Wearable Electronic Devices
/ wearable sensors
2021
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Using Wearable Sensor Technology to Measure Motion Complexity in Infants at High Familial Risk for Autism Spectrum Disorder
by
Smith, Beth A.
, Elashoff, David
, Safari, Tabitha
, Wilson, Rujuta B.
, Vangala, Sitaram
in
Age
/ Autism
/ autism spectrum disorder
/ Autism Spectrum Disorder - diagnosis
/ Autism Spectrum Disorder - genetics
/ Babies
/ Cognition
/ Early childhood education
/ Genetic Predisposition to Disease
/ Humans
/ Infant
/ Longitudinal studies
/ Motor ability
/ motor development
/ Preschool children
/ quantitative measures
/ Sensors
/ Standard scores
/ Technology
/ Wearable Electronic Devices
/ wearable sensors
2021
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Using Wearable Sensor Technology to Measure Motion Complexity in Infants at High Familial Risk for Autism Spectrum Disorder
by
Smith, Beth A.
, Elashoff, David
, Safari, Tabitha
, Wilson, Rujuta B.
, Vangala, Sitaram
in
Age
/ Autism
/ autism spectrum disorder
/ Autism Spectrum Disorder - diagnosis
/ Autism Spectrum Disorder - genetics
/ Babies
/ Cognition
/ Early childhood education
/ Genetic Predisposition to Disease
/ Humans
/ Infant
/ Longitudinal studies
/ Motor ability
/ motor development
/ Preschool children
/ quantitative measures
/ Sensors
/ Standard scores
/ Technology
/ Wearable Electronic Devices
/ wearable sensors
2021
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Using Wearable Sensor Technology to Measure Motion Complexity in Infants at High Familial Risk for Autism Spectrum Disorder
Journal Article
Using Wearable Sensor Technology to Measure Motion Complexity in Infants at High Familial Risk for Autism Spectrum Disorder
2021
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Overview
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.
Publisher
MDPI AG,MDPI
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