  Studies have shown that children can be exposed to smart devices at a very
early age. This has important implications on research in children-computer
interaction, children online safety and early education. Many systems have been
built based on such research. In this work, we present multiple techniques to
automatically detect the presence of a child on a smart device, which could be
used as the first step on such systems. Our methods distinguish children from
adults based on behavioral differences while operating a touch-enabled modern
computing device. Behavioral differences are extracted from data recorded by
the touchscreen and built-in sensors. To evaluate the effectiveness of the
proposed methods, a new data set has been created from 50 children and adults
who interacted with off-the-shelf applications on smart phones. Results show
that it is possible to achieve 99% accuracy and less than 0.5% error rate after
8 consecutive touch gestures using only touch information or 5 seconds of
sensor reading. If information is used from multiple sensors, then only after 3
gestures, similar performance could be achieved.
