BOPETRACKER: PREGNANCY TRACKING APP
| dc.contributor.author | Yessimkhanov, Aldiyar | |
| dc.contributor.author | Issatay, Ayan | |
| dc.contributor.author | Aliyev, Meiir | |
| dc.contributor.author | Skakov, Madi | |
| dc.contributor.author | Dunaitsev, Maxim | |
| dc.date.accessioned | 2025-06-11T14:27:29Z | |
| dc.date.available | 2025-06-11T14:27:29Z | |
| dc.date.issued | 2025-04-25 | |
| dc.description.abstract | BopeTracker is a comprehensive mobile app to help pregnant women throughout the entire term of their pregnancy by integrating health monitoring, personalized content, and partner engagement in one seamless user platform. Inspired by the fragmentation of current tools—each often requiring the switching of multiple applications or manual entry—this senior project uses a cross-platform Flutter frontend and Node.js/Express backend with PostgreSQL to provide robust, scalable capabilities. Noteworthy capabilities include weekly fetal development milestones, customizable health trackers (kick counter, contractions, weight, sleep), clinical protocol-driven calendar reminders, secure medical record and journal entry storage, and on-demand guidance from an AI-powered doctor chatbot. Partner access allows the sharing of milestones and health measurements in real time, to provide both emotional and logistical support. Agile development with role-based tasks allowed parallel frontend and backend streams, version control using GitHub, and iterative user testing at a mother-child center. Core capabilities were tested with five participants and offered concrete feedback on design, personalization, postpartum, as well as wearable device and marketplace integrations. Results of testing indicate high satisfaction with the AI chatbot, calendar, and partner components, while also revealing opportunities for much greater UI personalization, postpartum-related modules, and data interoperability. Future development will see the addition of clinical portal integration, predictive analytics, offline capabilities, and more stringent AI moderation to prevent hallucinations, thus moving the state of maternal health technology forward. | |
| dc.identifier.citation | Yessimkhanov, A., Issatay, A., Aliyev, M., Skakov, M., & Dunaitsev, M. (2025). BopeTracker: Pregnancy tracking app. Nazarbayev University School of Engineering and Digital Sciences. | |
| dc.identifier.uri | https://nur.nu.edu.kz/handle/123456789/8874 | |
| dc.language.iso | en | |
| dc.publisher | Nazarbayev University School of Engineering and Digital Sciences | |
| dc.rights | Attribution-NonCommercial-ShareAlike 3.0 United States | en |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-sa/3.0/us/ | |
| dc.subject | Pregnancy Tracking | |
| dc.subject | Mobile Health Application | |
| dc.subject | AI-Powered Chatbot | |
| dc.subject | Flutter Cross-Platform Development | |
| dc.subject | type of access: open access | |
| dc.title | BOPETRACKER: PREGNANCY TRACKING APP | |
| dc.type | Bachelor's Capstone project |
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