Physiogame

Inspiration

A teammates injury and improper workouts and posture led to further injury.

What it does

Our app uses a computer vision model to detect the poses and movements a user is doing and helps correct it to make physiotherapy safer at home as well as more engaging experience using gamification.

How we built it

We used python mediapipe and the Unity Mediapipe Body plugin to send pose data and get the gamification of the Unity game engine.

Challenges we ran into

• Getting the AI model to recognize poses
• making sure all poses are possible
• communication between two programming languages

Accomplishments that we're proud of

• Getting a fully working computer vison model
• Finishing a fully working figma prototype
• Being able to fit into the time constraints of the hackathon
• being able to get valuable insights from industry professionals

What we learned

• Computer vision
• Design with figma
• Scheduling
• the value of peoples insights

What's next for Physiogame

We are looking to commercialize Physiogame and partner with clinics to get this in public testing to see what we can improve and how we can further help in the industry.

Built With

• mediapipe
• opencv
• python
• unity