Ira L. Cohen and colleagues from the New York State Institute for Basic Research in Developmental Disabilities presented their research on video tracking as a valuable way to study autism spectrum disorders (ASD) at last month’s International Meeting for Autism Research (IMFAR).
Using EthoVision XT, a video tracking software that analyzes behavior, movement, and activity, the team examined correlations between data from various ASD rating scales (including the PDD Behavior Inventory™ [PDDBI™]), and information gathered through video tracking. Researchers studied 31 children between the ages of 2 and 14 in a large room with toys on the floor and on a table. Twenty-two of the children in the study were diagnosed with an ASD. The child’s parent was seated in the corner of the room during the free play time. Data was collected on mean distance from the parent, mean time spent in different zones in the room, path complexity, and other factors.
Researchers were able to draw correlations between the tracking data and the results on the rating scales, finding that the tracking data could be used as a predictor of the scores on the rating scales. Results from this study may be a basis for creating new objective methods of assessing children with ASD as well as measuring the results of intervention.