## Inspiration

Post operative care drastically improves the quality of life of individuals who have undergone surgery. When completed routinely, post operative care not only increases the process of healing but also helps individuals regain their range of motion and return to their daily activities faster.

So why do people need an app for this? Why not just call mom?

People often forget about the numerous medications (frequency, refills...), rehabilitation instructions, physiotherapy appointments and the different types of exercises they require before and after surgery. OpBuddy is here to solve that!

## What it does

OpBuddy organizes a patient's rehabilitation details and medication in one simple app. Users can take a photo of their operative care instructions (pre and post) and prescription forms. This information will become reminders for the patient to take their medication, refill their prescriptions, and to also prepare for operative care. Users can see their calculated coverage to provide more transparency with the hidden costs of medical procedures including pre and post-op medication,and rehabilitation appointments. OpBuddy calculates third party insurance coverage and keeps a cumulative total of running costs for users to ensure better budgeting. OpBuddy also reminds users of upcoming doctors appointments with the date, location and time to ensure a user never misses an appointment!

## How we built it

Prototype completed on Adobe XD.
Programmed using React, Node.js, JavaScript and the Azure Computer Vision API.

## Challenges we ran into

Difficulties with API integration.

## Accomplishments that we're proud of

Integrating the Azure Computer Vision API to successfully function with the app.

## What we learned

Front-end design, API integration, using Azure APIs.

## What's next for OpBuddy

Calendar syncing with the Google Calendar API such that users can ensure that their appointments are not clashing with any other aspect of their life. We also hope to enable family sharing between patients and their loved ones for more seamless healthcare. For more geriatric populations, loved ones can check whether the patient has taken their medication, when their appointments are and when to go for refills.
## Inspiration

This project came to us when one of our teammates mentioned his grandma struggling to keep track of her cholesterol and the medications she was taking to lower it. We realized that to help alleviate this, we would need to approach the problem from both sides.

High blood cholesterol causes **4.4 million** deaths each year (World Heart Federation, 2019), and other nutrient deficiencies and surplusses take many more. By leveraging new multimodal LLMs, we set out to solve this complex and multi-faceted problem.

## What it does

MultiMed Vision+ allows users to track both their medications and nutrients with the snap of a picture. It then uses the information scanned by the user to generate advice in the context of the user's current health situation. MultiMed Vision+ integrates with our Raspberry Pi "watch", desktop app, and mobile app, easing access and user-friendliness for this demographic.

The project comprises several key components, including:

Integration of Prescription and Nutrition Data:
Incorporating scanned prescriptions and food items to provide personalized recommendations based on individual health contexts.
Analyzing prescription data to offer tailored health advice and reminders related to medication adherence.

Smartwatch Integration:
Facilitating easy access to health data without the need for a smartphone.
Streamlining the monitoring of vital health indicators for elderly individuals.

User-Friendly Interface:
Designing an intuitive and straightforward interface specifically tailored to the needs of older users.
Offering clear and concise advice on dietary choices and providing real-time health monitoring.

Real-Time Sensor Data Analysis:
Utilizing machine learning models integrated with real-time sensor data to predict the risk of heart attacks.
Providing timely alerts and notifications to both the user and their family members, enabling proactive health management and intervention.

## How we built it

Our project is split into a frontend and a backend stack. Our front end includes all of our UI/UX designs, and it utilizes Next.js + Typescript to build a UI design. It has authentication from Firebase + Clerk.js, and uses Tailwind CSS for styling. In the backend, we have our machine learning pipeline in Python as well as our API routes through FastAPI. We utilized OpenAI, Azure AI, Hugging Face, and Intersystems IntegratedML.

## Challenges we ran into

One of the main issues we ran into was understanding and integrating InterSystems into our product. Since it was the first time our entire team was working with the IntegratedML tool, we had to spend quite a bit of time debugging and reading tool documentation to understand how we could implement this pipeline.

## Accomplishments that we're proud of

We were able to simulate a real-life scenario where a user could scan their prescription and dishes from either their smartwatch (simulated through a raspberry pi) or mobile phone seamlessly. The integration of our tool into a wearable device allows a user to go about their entire day while also keeping track of their health in just a few seconds. We were able to hyper-personalize our context window and integrate an ML model so that our tool could give reliable insights to users based on their pre-existing conditions and eating habits.

## What we learned

We learned a lot about integrations with different systems and models. Specifically, we learn how to use InterSystems as well as integrations with Raspberry Pi.

## What's next for MultiMed Vision+

The next step for MultiMed Vision is to launch this idea fully, expanding our vast data sources and improving on our hardware + software systems. Moreover, we are looking to consider expanding our platform that can tell us more about where our food came form, such as where it's being produced/processed. We could potentially integrate with blockchain technology by briding the real world with web&web3.
## Inspiration

As university students, we understand that studying can be difficult. Doing your assignments by yourself is boring and sometimes unrewarding. Yet, most of the time, working with your friends just ends up with no work being done. Thus, we wanted to create the perfect companion that would provide optimal study support for students and their needs. Then we came up with Study \_Bae\_max.

## What it does

To start, Study Baemax may be turned on by a fingerprint sensor on his hand. Baemax will monitor you as you study, sensing whether you are still working on your assignments or tasks. If you are not, Baemax will say something mean to you, but if you are and you finish a task, Baemax will give you a little treat!

## How we built it

The body of Baemax was intended to work like a vending machine that would dispense treats. We were fortunate enough to have the chance to work with the Qualcomm HDK8450, and we wanted to utilize it as the interface for Baemax.

## Challenges we ran into

Understanding how to use the parts of Qualcomm and trying to connect all the peripherals was more difficult than anticipated. Regarding the Qualcomm, much of the difficulty arose from being inexperienced with the

## Accomplishments that we're proud of

We were able to connect the Qualcomm to our laptops, which was very difficult. Each small step along the way was extremely satisfying. We're also very proud that we were able to tackle on a project where many of us were inexperienced, especially in working with the hardware.

## What we learned

We learned a lot about how to make apps, use Qualcomm, and also the process in making a vending machine mechanism. We also learned that next time, it would be wiser to plan out our project so that we can start the parts that take longer earlier, such as developing the app or physically putting together the project. We also learned a lot about how to connect arduinos to peripherals.

## What's next for Study Baemax

We would like to refine our project further including making the app work and also making Baemax look more friendly.