Health Habit Hub gives you the tools to design studies, guide cohorts and analyse data in a privacy-compliant way. The technical infrastructure runs in the background so you can focus on the research question.

One dashboard for everything: configure studies and questionnaires, maintain the shared knowledge base, track participant progress and export data.
Every building block has a clear job, and all of it runs on its own controlled infrastructure at TU Dresden. That means reproducible results, traceable data paths, and no dependence on an outside vendor that changes the rules tomorrow.
It all starts in the admin portal: you create your study, define the habits and the consent form, and get a study code for your participants.
Participants download the app and enter your study code to join. The same codebase runs on iOS, Android and the browser, so no one is excluded and your sample is not skewed by platform.
Sign-in and digital consent run through Keycloak. Participants, researchers and admins are cleanly separated, and no one sees more data than their role allows. This is the basis for a clean ethics approval.
Only after consent does a central service receive the data, validate it and enforce your study logic. Your study rules live in a single place instead of being scattered across many devices.
MongoDB stores the entries, Neo4j the relationship graph between habits. That split makes both classic statistics and network analysis possible, with no compromise.
The recommender suggests fitting habits to participants. For you as a researcher it is a controllable intervention whose effect you can measure in the same system.
At the end of the chain, everything runs behind a reverse proxy with TLS on a TU Dresden server. The data never leaves university infrastructure, and you stay independent of commercial providers.
Create studies, split participants into cohorts and steer interventions, with no detours.
Established instruments like the Self-Report Habit Index, collected automatically across the study.
A shared knowledge base feeds the recommendations participants receive in the app.
Structured exports for your analysis in R, Python or SPSS, with no direct database access.
Keep operational health and metrics in view via Grafana while the study runs.
A clean split between admin, researchers and participants via Keycloak, secured with single sign-on.
Whether it is your own study, a collaboration, or just a question, send us a few lines and we will get back to you.