Toward the Autism Motor Signature: Gesture patterns during smart tablet gameplay identify children with autism.

ABSTRACT: Autism is a developmental disorder evident from infancy. Yet, its clinical identification requires expert diagnostic training. New evidence indicates disruption to motor timing and integration may underpin the disorder, providing a potential new computational marker for its early identification. In this study, we employed smart tablet computers with touch-sensitive screens and embedded inertial movement sensors to record the movement kinematics and gesture forces made by 37 children 3-6 years old with autism and 45 age- and gender-matched children developing typically. Machine learning analysis of the children's motor patterns identified autism with up to 93% accuracy. Analysis revealed these patterns consisted of greater forces at contact and with a different distribution of forces within

SUBMITTER: Anzulewicz A 

PROVIDER: S-EPMC4995518 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature