This paper develops the Adaptive Multisensory Integration Framework (AMIF), explaining how artificial intelligence coordinates sensory modalities to enhance human-computer interaction. Synthesizing cognitive neuroscience, AI, and HCI theories, AMIF identifies five cyclically-operating components governing multisensory integration. Critical analysis reveals fundamental limitations in temporal prediction, computational efficiency, and individual variability. Four case studies demonstrate the framework's explanatory power, showing both successes and persistent challenges in real-world systems. The framework generates testable hypotheses and design principles grounded in theoretical understanding.
목차
Abstract 1. Introduction 2. Theoretical Foundations 2.1 Cognitive Neuroscience Principles 2.2 Artificial Intelligence and HCI 2.3 AMIF in Context: Comparison with Existing Frameworks 3. The Adaptive Multisensory Integration Framework 4. Case Studies: Applying AMIF 4.1 SYNC-VR: Motion Sickness Reduction 4.2 Multisensory Balance Training for Multiple Sclerosis 4.3 Text-to-Haptics: Emotional Congruence 4.4 CNN-Based Multisensory Enhancement 5. Critical Analysis and Design Principles 6. Conclusion References