Inclusive Kitchen Design for Older Adults: Generative AI Visualizations to Support Mild Cognitive Impairment
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Abstract (arXiv)
Mild Cognitive Impairment (MCI) affects 15-20% of adults aged 65 and older, often making kitchen navigation and independent living difficult, particularly in lower-income communities with limited access to professional design help. This study created an AI system that converts standard kitchen photos into MCI-friendly designs using the Home Design Guidelines (HDG). Stable Diffusion models, enhanced with DreamBooth LoRA and ControlNet, were trained on 100 kitchen images to produce realistic visualizations with open layouts, transparent cabinetry, better lighting, non-slip flooring, and less clutter. The models achieved moderate to high semantic alignment (normalized CLIP scores 0.69-0.79) and improved visual realism (GIQA scores 0.45-0.65). In a survey of 33 participants (51.5% caregivers, 36.4% older adults with MCI), the AI-modified kitchens were strongly preferred as more cognitively friendly (87.4% of 198 choices, p < .001). Participants reported high confidence in their kitchen choice selections (M = 5.92/7) and found the visualizations very helpful for home modifications (M = 6.27/7). Thematic analysis emphasized improved visibility, lower cognitive load, and greater independence. Overall, this AI tool provides a low-cost, scalable way for older adults and caregivers to visualize and implement DIY kitchen changes, supporting aging in place and resilience for those with MCI.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 10 of its 26 references that are in the map. First posted on arXiv 14 Apr 2026.
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10 of 26 references.
References · 10
- 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
- 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
- 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
- 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
- 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
- 2022LAION-5B: An open large-scale dataset for training next generation image-text modelscited by 4,131
- 2019Generating Diverse High-Fidelity Images with VQ-VAE-2cited by 1,376
- 2019Improved Precision and Recall Metric for Assessing Generative Modelscited by 925
- 2018Assessing Generative Models via Precision and Recallcited by 401
- 2020GIQA: Generated Image Quality Assessmentcited by 51
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- 2025Exploring Object Status Recognition for Recipe Progress Tracking in Non-Visual Cooking
- 2024Emerging Practices for Large Multimodal Model (LMM) Assistance for People with Visual Impairments: Implications for Design
- 2025OSCAR: Object Status and Contextual Awareness for Recipes to Support Non-Visual Cooking
- 2023Large Language Models in Medical Term Classification and Unexpected Misalignment Between Response and Reasoning
- 2025Integrating Reinforcement Learning and AI Agents for Adaptive Robotic Interaction and Assistance in Dementia Care
- 2025Beyond Visual Perception: Insights from Smartphone Interaction of Visually Impaired Users with Large Multimodal Models