Deep Generative Visual Therapy: GAN-Driven Image Generation for Cognitive Support in ASD

Abstract

Children with Autism Spectrum Disorder (ASD) benefit from personalized visual and cognitive stimulation. We present Deep Generative Visual Therapy (DGVT), an interactive system using Generative Adversarial Networks (GANs) to create tailored visual content for stimulating children with ASD. Our method features a custom GAN architecture trained with symbolic and concrete images to generate suitable stimuli for therapy targets such as attention enhancement, visual sequencing, and pattern matching. The system, built on TensorFlow and Keras, is accessible via Google Colab for real-time control and customization by therapists and educators. A series of cognitive games using generated images supports attention, visual discrimination, and memory. Initial assessments with therapists and pilot users showed positive engagement, indicating GAN-generated stimuli can complement traditional cognitive therapy for ASD. This effort connects generative deep learning with neurodevelopmental treatment to apply adversarial image synthesis in practical sensory and human-centered applications.