Design Research on an AI-Assisted Everyday Food Therapy Service System: A Case Study of the "Food Rhythm" Digital Food Therapy 4S Store
Abstract
This study addresses three problems in everyday food therapy services: insufficient explanation of recommendations, weak continuity between digital advice and offline fulfilment, and unclear boundaries of AI assistance. Taking the "Food Rhythm" Digital Food Therapy 4S Store as a design case, this research adopts a research-through-design approach that combines literature review, competitor analysis, semi-structured interviews, and service system design. The proposed system connects low-burden need expression, explainable AI recommendation, physical constraint-card interaction, offline ingredient display, open preparation, and feedback. Its core design logic is to treat AI not as a medical decision-maker, but as an auxiliary service capability that helps users understand, adjust, verify, and continue everyday food-therapy suggestions. By coordinating the mobile app, interaction terminal, physical cards, store environment, and backstage support, the design translates algorithmic output into an inspectable service journey. The study contributes a service-system framework for applying AI to daily health-related services while maintaining transparency, user control, and non-medical safety boundaries.
References
- Celis-Morales, C., Livingstone, K. M., Marsaux, C. F. M., et al. (2017). Effect of personalized nutrition on health-related behaviour change: Evidence from the Food4Me European randomized controlled trial.International Journal of Epidemiology, 46(2), 578-588. https://doi.org/10.1093/ije/dyw186
- Min, W., Jiang, S., & Jain, R. (2020). Food recommendation: Framework, existing solutions, and challenges.IEEE Transactions on Multimedia, 22(10), 2659-2671. https://doi.org/10.1109/TMM.2019.2958761
- Longoni, C., Bonezzi, A., & Morewedge, C. K. (2019). Resistance to medical artificial intelligence.Journal of Consumer Research, 46(4), 629-650. https://doi.org/10.1093/jcr/ucz013
- Wang, L., Zhang, Z., Wang, D., et al. (2023). Human-centered design and evaluation of AI-empowered clinical decision support systems: A systematic review.Frontiers in Computer Science, 5, 1187299. https://doi.org/10.3389/fcomp.2023.1187299
- Loh, H. W., Ooi, C. P., Seoni, S., et al. (2022). Application of explainable artificial intelligence for healthcare: A systematic review of the last decade (2011-2022).Computer Methods and Programs in Biomedicine, 226, 107161. https://doi.org/10.1016/j.cmpb.2022.107161
- De Croon, R., Segovia-Lizano, D., Finglas, P., Vanden Abeele, V., & Verbert, K. (2025). An explanation interface for healthy food recommendations in a real-life workplace deployment: User-centered design study.JMIR mHealth and uHealth, 13, e51271. https://doi.org/10.2196/51271
- International Organization for Standardization. (2019).ISO 9241-210:2019 Ergonomics of human-system interaction-Part 210: Human-centred design for interactive systems. International Organization for Standardization.