What is it about?
Most wellness apps give the same suggestions to everyone. They rarely adjust when your habits change. They often rely on collecting your personal data in one place, which can create privacy risks. This paper introduces a new kind of AI system a Self-Healing Digital Twin that learns from your daily routines, adapts to your changing health patterns, and protects your privacy at every step. The system creates a virtual model of each user based on information from wearables, activity logs, and basic health trends. This “digital twin” tracks things like sleep, movement, and mood changes. When the AI notices that something is off poor sleep, higher stress, lower activity it suggests small, personalized adjustments. Over time, the AI learns what actually works for each person and gives better recommendations. A major benefit is that the system never sees raw personal data. All sensitive information is removed before AI processing. Only anonymous patterns and trends are used, making the platform safer and easier to scale. We tested the system with simulations and with 3,000 real users on the Nutrosal platform. Engagement increased, and people stuck with healthy routines more consistently. The results show that adaptive AI can help people stay motivated and maintain long-term health habits while keeping their data private.
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Why is it important?
This work shows how wellness platforms can become far more effective by combining three capabilities that are rarely brought together: adaptive AI, real-time health monitoring, and strong privacy protection. Today’s health apps often fail because they use rigid, one-size-fits-all models, leading to low engagement and high dropout rates. Our system changes this by using reinforcement learning to continuously adjust recommendations based on real behavior. This improves user adherence by 30–45%, especially for people who typically disengage from wellness programs. The approach is also timely. People want personalized insights, but they are increasingly concerned about how much data apps collect. Our dual-cloud privacy architecture removes personal identifiers before any analysis occurs. This allows platforms to use powerful AI without risking user data exposure. By demonstrating strong results with both simulated and real-world data including higher engagement, better adherence, and lower dropout rates this work provides a blueprint for the next generation of trustworthy, adaptive, and privacy-focused health technologies.
Perspectives
This publication reflects years of effort in designing AI systems that truly adapt to people’s real habits while protecting their privacy. I wrote this paper to show that advanced AI can be personal without being intrusive. Building and testing this framework on a real wellness platform gave me a clear understanding of how people interact with AI-driven recommendations, and how small improvements in personalization can make a major difference in motivation and long-term success. I also hope this work helps shift the conversation in digital health. Personalization should not come at the cost of user privacy. By proving that a dual-cloud, privacy-preserving approach can still deliver strong AI performance, I aim to encourage more researchers and developers to adopt similar architectures. Most importantly, I hope this work reaches practitioners building wellness tools coaches, clinicians, and platform designers so they can apply these ideas to improve user engagement and help people live healthier lives.
Dr Nariman Mani
Nutrosal
Read the Original
This page is a summary of: Self-Healing Digital Twins: Hybrid Generative and Privacy-Preserving AI for Adaptive Wellness Platforms, June 2025, ACM (Association for Computing Machinery),
DOI: 10.1145/3721201.3725427.
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Resources
Nutrosal Research and Development
Nutrosal is social media-based platform through which it will offer consulting and coaching services related to nutrition by combining social networking and motivational groups with weight loss and fitness goals, members can connect with others who share similar objectives and foster mutual support. Utilizing cutting-edge AI techniques, the software will allow coaches and nutritionists to efficiently develop nutrition plans, while enabling members to receive prompt answers to their questions with minimal coach involvement. This application will also have groups and rooms where people with the same goals can connect and embark on a weight loss journey together. The food eaten needs to be logged into the application and the system will then warn the user if they have not been properly following the plan. This software is unique because it will integrate features for coaches, nutritionists, and clients, eliminating the need for separate systems. It will combine social networking, motivational groups, and fitness and weight loss goals. Members will be able to connect with others who have similar goals, fostering a sense of community and support. The software will make use of cutting-edge AI techniques to help coaches and nutritionists create nutrition plans quickly, while members get prompt responses to their inquiries with little help from coaches. The software will empower users to maintain their healthy behaviors even after reaching their goals by promoting a holistic approach to a healthy lifestyle that goes beyond diet and weight loss. Members will be able to easily track their progress and get support from their peers, while coaches and nutritionists can effectively manage the progress of their clients and offer tailored advice.
manistechmind - Nariman Mani
Nariman Mani, the mind behind “Mani’s Tech Mind.” I hold a PhD from Carleton University in Ottawa and bring more than 18 years of experience as a software QA specialist, engineer, architect, and technology leader. My work revolves around building resilient systems, guiding high-performing teams, and mentoring the next generation of engineers.
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