Swipe kinematic differences in young children with autism spectrum disorders are task- and age-dependent: A smart tablet game approach

Abstract

The motor system is becoming increasingly recognized as an important site of disruptions in autism spectrum disorders (ASD). However, the precise nature of this motor disruption remains unclear with some conflicted reports between papers. A bottleneck in kinematic studies of children with ASD has been the use of laboratory-based motion tracking systems and experimental paradigms that require didactic instructions. Thus, we employed an attractive smart tablet gameplay methodology to engage children’s interest without complicated verbal instruction. Children’s movements on the touch screen were recorded as they engaged in gameplay of their own volition, enabling improved ecological validity in data capture. Swipe kinematics were computed from two games that afforded goal-directed and free-style scribbling, respectively. 82 children aged 2-6 years were tested, including 37 children with ASD and 45 typically developing (TD) children. Kinematic analyses revealed significant age, group, and task differences. In comparison to aged-matched TD children, children with ASD under 5 years old performed faster goal-directed movements, whereas those over 5 years old performed slower goal-directed movements. In contrast, children with ASD moved faster than TD children irrespective of age during creative scribbling. Interestingly, movement speed increased with age in TD children in both game contexts, likely due to motor skill and confidence development, but this was not true for children with ASD, who moved slower in the case of goal-directed swipes or with no difference in the case of creative scribbling. These findings support emerging evidence for differences in maturation of visuomotor integration in preschool children with ASD.

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

“…The development of miniaturized inertial sensors, wearable sensors, and the ubiquity of mobile devices such as tablets and smartphones have allowed unprecedented access to massive multimodal data acquisition that has been used to characterize motor behavior. These data have been used to derive predictors of Parkinson's severity 35 , identify and quantify an autism motor signature and characterize the nature of motor impairments in autism [36][37][38][39][40][41][42][43][44][45] . These studies demonstrate the usefulness of tabletbased assessments and games for assessing motor skills.…”