Motivated by the lack of a suitable smartwatch solution for managing his son's Type 1 diabetes, a father embarked on building a custom smartwatch from scratch. Using off-the-shelf hardware components like a PineTime smartwatch and a Nightscout-compatible continuous glucose monitor (CGM), he developed software to display real-time blood glucose data directly on the watch face. This DIY project aimed to provide a discreet and readily accessible way for his son to monitor his blood sugar levels, addressing concerns like bulky existing solutions and social stigma associated with medical devices. The resulting smartwatch displays glucose levels, trend arrows, and alerts for high or low readings, offering a more user-friendly and age-appropriate interface than traditional diabetes management tools.
A developer created "Islet", an iOS app designed to simplify diabetes management using GPT-4-Turbo. The app analyzes blood glucose data, meals, and other relevant factors to offer personalized insights and predictions, helping users understand trends and make informed decisions about their diabetes care. It aims to reduce the mental burden of diabetes management by automating tasks like logbook analysis and offering proactive suggestions, ultimately aiming to improve overall health outcomes for users.
HN users generally expressed interest in the Islet diabetes management app and its use of GPT-4. Several questioned the reliance on a closed-source LLM for medical advice, raising concerns about transparency, data privacy, and the potential for hallucinations. Some suggested using open-source models or smaller, specialized models for specific tasks like carb counting. Others were curious about the app's prompt engineering and how it handles edge cases. The developer responded to many comments, clarifying the app's current functionality (primarily focused on logging and analysis, not direct medical advice), their commitment to user privacy, and future plans for open-sourcing parts of the project and exploring alternative LLMs. There was also a discussion about regulatory hurdles for AI-powered medical apps and the importance of clinical trials.
Summary of Comments ( 6 )
https://news.ycombinator.com/item?id=42854291
Hacker News commenters largely praised the author's dedication and ingenuity in creating a smartwatch for his son with Type 1 diabetes. Several expressed admiration for his willingness to dive into hardware and software development to address a specific need. Some discussed the challenges of closed-loop systems and the potential benefits and risks of DIY medical devices. A few commenters with diabetes shared their personal experiences and offered suggestions for improvement, such as incorporating existing open-source projects or considering different hardware platforms. Others raised concerns about the regulatory hurdles and safety implications of using a homemade device for managing a serious medical condition. There was also some discussion about the potential for commercializing the project.
The Hacker News post "Building a T1D smartwatch for my son from scratch" generated a substantial discussion with 29 comments. Many commenters expressed admiration for the author's dedication and ingenuity in creating a custom solution for managing his son's Type 1 diabetes.
Several commenters focused on the complexities and frustrations of dealing with existing diabetes technology. One user shared their personal experiences with closed-loop systems, highlighting the challenges of achieving optimal glucose control and the constant need for calibration and adjustments. They appreciated the author's proactive approach to building a tailored solution. Another commenter echoed these sentiments, emphasizing the limitations of current commercial offerings and the burden placed on users, particularly children.
Some commenters raised concerns about the project's safety and regulatory aspects. One user questioned the implications of relying on a self-built system for such a critical health condition and suggested exploring collaboration with medical professionals. Another commenter inquired about the device's accuracy and reliability, emphasizing the importance of rigorous testing and validation.
A few commenters offered technical suggestions and resources. One commenter mentioned alternative hardware platforms that might be suitable for the project. Another commenter shared a link to a relevant open-source project, potentially offering valuable insights and code examples.
Several users praised the open-source nature of the project, expressing hope that it could benefit other individuals with Type 1 diabetes. They appreciated the author's willingness to share their work and contribute to the community.
Some comments delved into the specific technical details of the project, discussing aspects such as data processing, algorithm design, and user interface development. These comments demonstrated a genuine interest in the project's technical implementation and offered valuable feedback to the author.
Overall, the comments reflect a mix of admiration, concern, and technical curiosity. The compelling comments highlight the challenges of managing Type 1 diabetes, the potential benefits of customized solutions, and the importance of collaboration and open-source development in addressing complex health problems. They also underscore the need for thorough testing and validation to ensure the safety and reliability of such systems.