Interior space design significantly influences residents' daily lives. However, the process often presents high barriers and complex reasoning for users, leading to semantic losses in articulating comprehensive requirements and communicating them to designers. This study proposes the Mental-Gen design method, which focuses on interpreting users' spatial design intentions at neural level and expressing them through generative AI models. We employed unsupervised learning methods to detect similarities in users' brainwave responses to different spatial features, assess the feasibility of BCI commands. We trained and refined generative AI models for each valuable design command. The command prediction process adopted the motor imagery paradigm from BCI research. We trained Support Vector Machine (SVM) models to predict design commands for different spatial features based on EEG features. The results indicate that the Mental-Gen method can effectively interpret design intentions through brainwave signals, assisting users in achieving satisfactory interior space designs using imagined commands.
[MM/AI] Mental Models in Human-AI Interaction: Methods and Challenges in the Generative and Agentic AI Era (Workshop)
Ludwig Maximilian University（路德维希-马克西米利安大学）；ETH Zürich（苏黎世联邦理工学院）；CSAIL, Massachusetts Institute of Technology（麻省理工学院计算机科学与人工智能实验室）；Technical University of Munich（慕尼黑工业大学）；Research Center Trust, University Duisburg-Essen（杜伊斯堡-埃森大学信任研究中心）；HCII, Carnegie Mellon University（卡内基梅隆大学人机交互研究所）；Microsoft（微软）
Cloning the Self for Mental Well-Being: A Framework for Designing Safe and Therapeutic Self-Clone Chatbots
University of British Columbia（不列颠哥伦比亚大学）；Johns Hopkins University School of Medicine（约翰斯·霍普金斯大学医学院）；City College of New York（纽约市立学院）；Korea Institute of Science and Technology（韩国科学技术院）
From Risk Avoidance to User Empowerment in AI Mental Health Crisis Support
Dartmouth College（达特茅斯学院）；Northwestern University（西北大学）；University of California San Francisco（加州大学旧金山分校）；University of Minnesota（明尼苏达大学）；Microsoft Research（微软研究院）；LivingWorks；Florida State University（佛罗里达州立大学）；Microsoft（微软）；Boston University（波士顿大学）；Johns Hopkins University（约翰斯·霍普金斯大学）；Mental Health America（美国心理健康协会）；University of Washington（华盛顿大学）
