NEUROADAPTIVE XR INTERFACES: A GENERATIVE AI FRAMEWORK FOR REAL-TIME EMOTION-AWARE PERSONALIZATION IN VIRTUAL AND AUGMENTED ENVIRONMENTS PRODUCING COGNITIVELY RESPONSIVE IMMERSIVE SYSTEMS

This paper introduces a neuroadaptive framework that enables emotion-aware personalization within extended reality (XR) environments by fusing brain-computer interfaces (BCIs), spatial AI, generative artificial intelligence, and embodied agents. As XR becomes increasingly immersive, systems that can interpret and adapt to users’ real-time cognitive and emotional states become essential for optimal human-computer interaction. We present a design where physiological signals—especially EEG and eye tracking—are analyzed in real-time and used to guide generative scene rendering and embodied conversational agent behavior. We contextualize the system within technological landscape, emphasizing recent advances in large multimodal models and wearable neural interfaces. Through a literature review grounded in work, we highlight foundational studies that underpin this approach. Furthermore, the paper provides a system architecture overview, proposes a validation framework, and discusses ethical and technical challenges. We conclude by identifying open challenges in deploying neuroadaptive XR at scale and suggest directions for future interdisciplinary research.