Inspiration

Inspired by personal experience and people in the surroundings with back pains (in urban cities, friends, students, and other youths). We identified chronic back pain in youth as an issue driven by the urban environment due to inactivity and heavy physical workload for students and youths under financial pressure (standing part-time job for example).

What it does

It is an app that provides users with prompts and results according to their answers. The result will suggest therapeutic movements, and general daily and sleeping suggestions specific to the user's pain condition. It also provides directions to connect with healthcare professionals.

How we built it

Our journey began with crafting the frontend using HTML, CSS, and Figma DevTools, streamlining the process of importing SVG icons for a sleek design. Transitioning to the backend, we chose Express.js for routing and basic functionalities, optimizing our mobile-exclusive application.

Express.js proved to be a powerhouse, enhancing functionality, and EJS came on board to handle proper image rendering. With a user-centric approach, we introduced an AI bot for engaging interactions. Elevating the backend, we integrated Cohere's rerank function to swiftly fetch pertinent information.

In a nutshell, our mobile app combines frontend creativity, Express.js robustness, AI-driven interactions, and Cohere's efficiency for a seamless user experience. The synergy of frontend and backend elements ensures a dynamic and user-friendly application. 🚀

Challenges we ran into

Navigating through our project, we encountered several challenges. First on the list was wrangling with frontend components, aligning them just right in the layout. The struggle was real, especially when it came to debugging and solving issues—like putting together a puzzle with missing pieces.

Diving into the backend brought new challenges, especially with APIs and data fetching. It felt like connecting the dots, making sure our app gets the right info at the right time. This puzzle went beyond the frontend, needing precision to make all the data fit perfectly.

Since it was my first time in the backend world, every challenge was a learning opportunity. Navigating through it all not only enriched my skills but also deepened my understanding of how things work behind the scenes. 🚀🧩

Beyond the code, time management emerged as a significant hurdle. Juggling various tasks, we aimed to deliver top-notch work before the deadline, adding that finishing touch to every detail.

On the EJS front, the challenge of incorporating the includes function added an extra layer. This function brought its own set of complexities, but tackling it head-on was essential for a seamless user experience.

In essence, our journey wasn't without its hurdles, but each challenge became an opportunity for growth and learning, ensuring our project reached its full potential. 🚀

Accomplishments that we're proud of

The application design and code implementations. The originality in approaching an urban issue that people often do not recognize, but connects to healthcare security/accessibility and the social well-being of youth.

What we learned

About the project: During this project, we learned how to make the most out of a team. We learned how to reach maximum potential by letting each member thrive on their roles and using strength. We learned from each other's personal and academic experiences with a great multidisciplinary approach. About urban topics: We learned the impact of chronic pain in the daily lives of the urban population and beyond as a healthcare crisis. An important association between sleep and back pain and how this can further affect one's well-being (mental health). And how the population suffering chronic back pains can be modeled by income in youth. It creates social gaps in well-being as good healthcare accessibility and pain management vary due to financial and political barriers in certain populations in the urban environment.

What's next for Thrive

Drive business opportunities by implementing subscriptions and memberships with successful use. Implement user's data-driven pain pattern and treatment efficacy recognition and movement detection AIs. Broaden body parts in prompts (not only back and neck but users can express pain in a wider range of body parts) and suggestions for treatment.

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