A Family Emotional Support System for MCS Patients Based on an EEG-to-Visual Translation Mechanism: Design, Implementation, and Preliminary Validation

(1) Patients in a minimally conscious state (MCS) and their families face prolonged emotional distress and psychological challenges due to the uncertainty of recovery and limited means of emotional communication. This study aims to develop an EEG-based emotion visualization system to support affected families by translating patients’ neural activity into perceivable emotional imagery. (2) Using simulated MCS patient EEG data corresponding to different emotional states, we designed a dynamic visual interface via TouchDesigner to convert bio-signals into real-time emotional animations. User tests involving questionnaires and interviews were conducted to evaluate the system’s performance. (3) The results demonstrate that the system accurately conveys emotional states, enhances caregivers’ perception of patients’ internal conditions, and significantly alleviates family members’ anxiety. (4) These findings suggest that EEG-based emotion visualization offers a viable and compassionate tool for supporting MCS families, providing new pathways for interdisciplinary research combining neuroscience and design while establishing a foundation for future clinical and home-care applications.