Impression

Inspiration

We were inspired by the potential to leverage technology to provide early detection of dementia, which can significantly improve patient outcomes through early intervention.

What it does

Impression is an innovative iPad app that accurately predicts early onset dementia by analyzing drawing motions, such as pencil pressure and jerk.

How we built it

We built Impression using advanced machine learning algorithms to analyze data collected from the iPad's touch sensors, focusing on drawing motions to identify early signs of dementia.

Challenges we ran into

We faced challenges in ensuring the accuracy of our predictions, integrating complex machine learning models with the app, and collecting sufficient data for training.

Accomplishments that we're proud of

We're proud of developing a highly accurate prediction model and creating a user-friendly interface that can assist in early dementia detection.

What we learned

We learned the importance of interdisciplinary collaboration, the intricacies of machine learning in medical applications, and the value of user-centric design.

What's next for Impression

Next, we plan to validate our app with clinical trials, enhance its features based on user feedback, and explore partnerships with healthcare providers for wider adoption.