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Christina Kaenmuang

Symprove

Symprove (Symptoms Improve) is a digital alternative to clinical IBS management. Inspired by evidence-based clinical protocols, it is designed for people who are struggling to access a dietitian, whether due to long waiting lists, cost, or availability and removes the friction of pen-and-paper journaling.

Features:
- Browse 200+ low-FODMAP recipes sourced from A Little Bit Yummy
- Follow the guided 3-step FODMAP protocol inspired by Monash University (elimination → reintroduction → personalisation)
- Browse an index of 400+ ingredients with FODMAP ratings
- Log meals with AI-assisted ingredient suggestions and camera scanning
- Log symptoms and track your history with trend charts, a calendar view, and food-symptom correlation analysis

Image showing thumbnail of app features
recipe page
Recipes page with quick filtering chips & fuzzy search
ingredient index
Ingredient index screen with detailed FODMAP classifications
symptom logging
Symptom logging modal, onces logged symptoms with correlate with meals, resulting in a "can eat" or "can't eat" indicator
The video shows the AI Intregated ingredient suggestion
fodmap protocol
FODMAP Protocol screen displaying tested FODMAP subgroups & results derived from correlation
Objectives

The aim of this project is to develop a mobile application that supports individuals with IBS
through the complete low-FODMAP dietary protocol, providing guided food reintroduction,
recipe discovery, meal logging, and symptom tracking within a single cohesive system.

Thesis: Symprove

The research carried out for this thesis focused on clinical treatments for IBS and the best way to incorporate those findings into a mobile app. This included the low-FODMAP diet and the protocols for each phase (elimination, reintroduction, and personalisation), symptoms and food correlation specific to each individual’s IBS type, and potential outliers such as stress and sleep quality.

On the technical side, the database schema and values were built from scratch, with web scraping implemented to speed up the process.

To find out more about this project please read the thesis below:

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Christina Kaenmuang
BSc (Hons) Creative Computing

Christina is a Creative Computing graduate. Throughout her degree, she has developed a strong foundation in full-stack development, data analytics, and a growing focus on AI.

BSc (Hons) Creative Computing