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Kid on The Phone! Toward Automatic Detection of Children on Mobile Devices
Toan Nguyen, Aditi Roy, Nasir D. Memon ·
Summary
Written by AI, not yet AICS's view · claude-haiku-4-5-20251001This technical paper describes methods to automatically detect whether a child or adult is using a mobile device by analyzing touchscreen behavior and sensor data. The researchers tested their detection algorithms on 50 children and adults using smartphones and achieved high accuracy in distinguishing between the two groups. The work aims to support child safety systems and child-computer interaction research.
Key points
- Detection achieved 99% accuracy using only touch information after 8 consecutive gestures
- Similar performance achieved with 5 seconds of sensor reading or 3 gestures with multiple sensors
- Dataset created from 50 children and adults interacting with off-the-shelf smartphone applications
- Behavioral differences between children and adults were extracted from touchscreen and built-in sensor data
Limitations
This is a technical feasibility study focused on detection methodology rather than an evaluation of a child safety or well-being intervention. The document does not assess actual impacts on children's safety, development, or well-being outcomes.
Abstract
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.