gym trAIner

Inspiration

When I first started working out, I didn’t have a clear understanding of what to do to achieve my goals or if I was performing the exercises correctly. This inspired me to create something that could guide beginners and experienced athletes alike, ensuring they’re on the right path and executing exercises safely and effectively.

What it does

Gym trAIner acts as a virtual fitness coach, analyzing workout techniques and suggesting improvements. It provides feedback on exercise form, tracks progress, and helps users achieve their fitness goals through a guided, data-driven approach.

How we built it

I built Gym trAIner using a combination of machine learning algorithms for motion analysis and a mobile app interface to interact with users. The app captures workout data through the device’s camera, which is processed to detect form and identify areas for improvement. We used Python and relevant machine learning libraries to develop the backend, while the frontend was designed to be user-friendly for easy navigation and real-time feedback.

Challenges we ran into

One major challenge was accurately identifying and analyzing various exercises across different body types and backgrounds. Fine-tuning the model to provide reliable feedback while accounting for individual differences required extensive data collection and iteration.

Accomplishments that we're proud of

I'm proud to have created an app that can offer actionable insights and guidance for fitness enthusiasts. Being able to bridge technology and fitness in a way that’s accessible and effective for users has been a rewarding achievement.

What we learned

I learned a lot about applying machine learning in a real-world setting, especially in a way that provides users with helpful insights. Additionally, working on this project improved our skills in mobile app development and helped us understand the challenges of fitness tech development.

What's next for gym trAIner

Our next steps are to improve the accuracy of the form analysis, expand the library of exercises supported, and potentially add features like goal tracking, personalized workout plans, and integration with other fitness platforms for a more comprehensive user experience.

Built With

• python
• vscode