Early screening and assessment of children with autism are crucial. Traditional methods primarily focus on observable behaviors and surface-level traits, while often overlooking core symptoms and underlying neurological mechanisms. These approaches typically rely heavily on the evaluator’s expertise and experience, making the results prone to subjectivity and limiting their ability to fully and accurately reflect a child’s cognitive and developmental status.

The Star Future Child Assessment System is designed for children aged 3 to 6 and employs a dual-dimensional, quantitative evaluation framework that integrates both external behavioral performance and internal brain responses. It offers comprehensive, data-driven, and timely assessments tailored to the needs of children with autism. By combining intelligent behavior-sensing technology with gamified assessment methods, the system quantifies learning processes and links them to learning outcomes, delivering more detailed and reliable results that align closely with standardized evaluation scales.

In addition, the system introduces an innovative method for accurately factorizing dynamic EEG data without relying on prior knowledge. This supports the creation of a self-adaptive deep learning model capable of precisely assessing functional brain states in children with autism. The insights gained from this dual-dimensional assessment are used to guide personalized, adaptive interventions, better supporting the individual learning and developmental needs of each child.