Project Info

Pulsify (Personal Health Log)

Devpost

Inspiration

We searched the internet for ideas and came across several medical-related ideas. A lot of the ideas involved the usage of AI, helping improve the efficiency of medical health workers, etc. Then we started brainstorming, what if we created a website that helped patients remember exactly when they experienced symptoms?

What it does

Pulsify is a website that takes in user input (text/speech) and automatically logs down the symptom felt on the right day in the calendar. Through this way, the patient can accurately "recall" when symptoms occurred when visiting health professionals. This ensures a higher chance for quicker and accurate diagnosis. There's other features like the dark/light mode, login/logout, heat map, and live chat. The heat map color codes separate calendar based on how many symptoms were logged on that day. The live chat is an AI bot that takes in user input. They can also log in symptoms for you in the calendar.

How we built it

We started by inputting the basic folders and files into VSCode. Then, we created our own individual branches and began coding. Whenever we added a feature, we saved, committed, and pushed to our own branches. After we achieved most of our baseline features, we merged the 3 branches together and began debugging the main branch together as a group. We maintained constant communication to help speed up our debugging process.

Challenges we ran into

We ran into merge conflicts. We all independently worked on our own branches, but didn't merge the changes while they were still little. As a result, it was more difficult to navigate through all the new files and folders when debugging and adding new features. For instance, we had accidentally created 2 different aspects of the navbar separately and they overlapped each other, preventing the interaction of some buttons.

Accomplishments we're proud of

We are all relatively very new to hackathons, so we're proud of producing a website with this much capability in a short time. We're also proud of our drive to keep coding through the night and motivation to fix our bugs.

What we learned

Not only did we learn how to code in new languages or build new features we've never done before, we learned how to collaborate efficiently. Whether it was through how GitHub operates, we learned that taking initiative is key to improving and developing our project. Regular communication and group agreement on ideas is equally as important as to prevent multiple people from working on the same things together.

What's next

We plan on debugging and beta testing the website for further improvements. Once that is done, we plan to add more features or expand our project scope, such as the following: Turn this website into a downloadable app available on all platforms/browsers and devices Improving the features to make usage of the website more intuitive for users Improve the accessibility within our website (apply WCAG AA standards) Add on MFA for extra security

Analysis

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Metric

Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.

Technology

Found in codeClaimed only
  • CSSIn code
  • Google GeminiIn code
  • JavaScriptIn code
  • MongoDBIn code
  • Next.jsIn code
  • ReactIn code
  • Tailwind CSSIn code
  • TypeScriptIn code
  • HTMLClaimed

8 of 9 appear in the indexed code. 1 claimed on Devpost could not be matched to code, which may simply mean the tool leaves no trace in the repository.

AI coding agents

No AI coding agent signals were found in this repository.

Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.

Codebase size

Source size

139 KB

Source files

40

Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.

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