Inspiration behind ProjectTibia.

Although we started with something else in our minds, while going through the documentation - we landed on the website of NewYork-Presbyterian where a story about Tibial Pseudoarthrosis captured not only our attention but also our hearts. We set forth to make diagnosis of the said condition not only cheaper, but faster and reliable as well.

What it does?

Our project uses Microsoft Kinect to capture and analyze various aspects of the subject such as the length of the tibial bone, ratio of the tibial bone of the left and the right leg and the amount of swing achieved by the knee joint. Using these metrics, we obtain an arbitrary score which we normalized using data captured through 40,000+ samples taken during the Hackathon where the attendees were observed for their walking pattern. This model is then compared with the live and average data taken from the subject during the test. If a deviation beyond a certain margin is observed, the application recommends consultation of a medical professional for confirmation of the disease.

How we built it?

The project makes use of Microsoft's Visual Studio and Kinect for Windows.

Challenges we ran into.

The biggest challenge we faced was to distinguish and teach our model, how to detect the presence of Tibial Pseudoarthrosis despite having access to the vast amount of healthy samples at the event which was a folly in itself. We did not have access to any of the prior medical history of any of our samples. Access to patients who tested positive to Tibial Pseudoarthrosis using conventional medical tests would go a long way in enforcing our model.

Accomplishments.

The accomplishment, we're most proud of, was the completion of our project.

Lessons.

Today, we got to learn about a lesser known disease that plagues our society and how it can be diagnosed in it's early stages apart from the technical know-how of using a Microsoft Kinect and it's dire potential in such applications.

What's next?

We would love to get access to some patients of whom, we have prior medical history. We hope that this project leads to a much needed disruption in the field of medical diagnosis through the use of ever-evolving computing devices.

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