Early screening and assessment of children with autism are very important. Traditional methods mainly focus on observable behaviors and surface traits but often miss core symptoms and underlying brain mechanisms. These methods also depend a lot on the evaluator’s experience, which can lead to subjective results and limit the accuracy of understanding a child’s cognitive and developmental status.

The Star Future Child Assessment System is designed for children aged 3 to 6 and uses a dual-dimensional, quantitative approach that combines both external behaviors and internal brain responses. It provides comprehensive, data-driven, and timely assessments tailored for children with autism. By integrating intelligent behavior-sensing technology with engaging, game-like assessment methods, the system measures learning processes and connects them with learning outcomes, offering more detailed and reliable results that align with standard evaluation scales.

Additionally, the system introduces a new way to analyze dynamic EEG data without needing prior information. This enables the creation of a self-adaptive deep learning model that accurately assesses brain function in children with autism. The insights from this dual-dimensional assessment help guide personalized and adaptive interventions, better supporting each child’s unique learning and developmental needs.