The O+ Project

Side view of model
Back view of Model
Front view of model
Inner components of Model
Parameters example
Parameters example pt.2
MyHealthOnline login and google cloud connection via RBC classification.
Red Blood Cell Count example

Inspiration

The general inspiration for this project is to help those who have recently received organ transplants. Unfortunately, in 15% of the organ transplant cases in the United States, there is acute rejection, meaning an outright rejection by the body for the organ being transplanted. We want to help detect this by measuring Red Blood Cell Counts and White Blood Cell Counts.

What it does

We have prototyped a model microscope that uses the camera features of a smartphone to zoom in and detect the number of Red and White blood cells depending on the kind of slide inserted. There are two slides that we are hoping to work with. One version of the slide does not use any form of dye or staining for Red Blood Cell Counting, and another version with a dye mixed in with blood that detects the white blood cell count.

How we built it

We built the 3-D model using Blender and the app model using Figma. We hope to use machine learning models to help with disease prediction and the prognosis of a disease in the future. Google Cloud and MyHealthOnline APIs will also be constructed into our app. They will be powerful and helpful tools for machine learning modeling and communicating data to doctors.

Challenges we ran into

Developing the hardware and the software. Unfortunately, due to a lack of resources, we could not develop a real-life prototype to demonstrate our technology. We would love to work on this in the future.

Accomplishments that we're proud of

We were delighted with how our 3-D model turned out and the basic design for the app. We want to work with more UI/UX designers to understand how to model this device and app. We also believe that our general idea was relatively simplistic and useful for patients of organ transplants. Furthermore, this idea can be implemented in various other diseases, such as RBC monitoring in bone marrow cancer.

What's next for The O+ Project

Developing the machine learning code and imaging technology is the next step in our project. We would like to also work on creating a more user-friendly experience when it comes to the device.