GatorAID

An AI-powered physical therapist that guides you through exercises, tracks your movements in real-time, and adjusts for mobility limitations—improving recovery and fitness from home.

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Inspiration

For our project, we aimed to incorporate computer vision into a website that could assist individuals in recovering from injury and pain. We envisioned creating software that tracks patient movements during exercises and ensures they achieve the necessary range of motion for optimal recovery. This solution bridges the gap between technology and physical therapy, making recovery more accessible from the comfort of one’s home.

What it does

GatorAID is an AI physical therapist tool that helps users recover from injury by informing them how to correctly do physical therapy exercises. Our website offers a wide range of guided recovery exercises tailored to different types of injuries or mobility issues. Using AI-driven computer vision, GatorAID monitors the user's form and provides real-time feedback to help ensure proper technique and movement. It also adjusts for any mobility limitations, providing an adaptive experience based on the user’s capabilities.

How we built it

We built GatorAid using a combination of front-end and back-end technologies. The front-end is powered by Python’s Streamlit, creating an intuitive and interactive user interface. On the back-end, we utilized Python along with Mediapipe and OpenCV for the computer vision components that track and analyze user movements in real-time.

Challenges we ran into

One major challenge we faced was integrating the front-end with the back-end. We needed to find a way to connect the computer vision algorithms running in Python to the base website. Another challenge was ensuring the accuracy of movement tracking, especially under different lighting conditions or camera angles. To bridge the gap between the Python back-end and the front-end, we tried using Flask, a lightweight web framework. However after running into a stream of technical issues we ended up using Python Streamlit to integrate the front end and back end of the website.

Accomplishments that we're proud of

We are proud of our "clap to start" system, which significantly improves the user experience by making it more intuitive and accessible. Additionally, we gained valuable skills in computer vision and learned how to build websites using React and Python.

What we learned

Throughout the project, we gained valuable knowledge on multiple fronts. We learned how to use React for web development, as it was a new tool for our team (However, we opted for Python). Additionally, we deepened our understanding of computer vision, particularly how to track human movements using libraries like Mediapipe and OpenCV. We also learned how to make a cohesive application that integrates front-end and back-end technologies, working through compatibility challenges to bring the solution to life.

What's next for GatorAID

Looking ahead, we plan to expand GatorAid by adding more exercises, especially targeting various muscle groups and injury types. We also aim to improve our tracking algorithms to handle more complex movements and introduce a more customizable experience for different levels of mobility. Eventually, we hope to collaborate with healthcare professionals to fine-tune the exercises and further enhance the accuracy of our AI feedback, making GatorAid a more comprehensive digital physical therapist.

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