• 

• 

• 

• 

Inspiration

In today’s fitness industry, there are countless apps designed to teach users the correct way to perform exercises. However, few apps provide real-time, personalized feedback that helps users improve their form by directly comparing it to professional standards. This gap inspired the creation of ProFormAI — a solution that not only instructs but also guides users throughout their fitness journey, ensuring they perform exercises with the correct form, improving both performance and reducing the risk of injury. ProFormAI focuses on making professional-level coaching accessible to everyone, offering actionable insights that adapt to each user’s specific needs and movements.

What it Does

ProFormAI empowers users by analyzing their workout videos and providing instant feedback on their form. Users can either upload pre-recorded videos or record their workouts in real-time using the app’s interface. The AI analyzes the user’s movements, compares them against professional standards, and offers detailed recommendations for improving posture, alignment, and overall technique. The app tracks progress over time, allowing users to see how their form improves.

Additional features include the ability to input workout schedules, with the app providing motivational quotes tailored to each user’s journey, keeping them inspired and on track. Over time, users receive personalized insights into their performance and areas for improvement, ensuring they stay motivated and engaged with their fitness goals.

How We Built It

We built ProFormAI using a combination of frontend and backend technologies to ensure a seamless user experience while leveraging advanced AI techniques for form analysis.

Frontend: Built with React, the user interface is intuitive and responsive, enabling users to upload workout videos or record workouts in real-time. We ensured compatibility across multiple devices and browsers, maintaining consistent functionality regardless of the platform being used.

Backend: We implemented a Flask backend that handles the video data processing and communication with the AI model. The backend is built in Python, enabling seamless integration with machine learning algorithms and ensuring that video data is processed efficiently.

AI Analysis: The core of our form analysis is built using a Random Forest Classifier from scikit-learn. The model was trained on a dataset of professional workout videos to accurately classify movements and assess user form. By comparing user movements with professional standards, the AI provides tailored suggestions on how to improve posture, technique, and balance for various exercises.

Additional Features: Users can input their workout schedules and receive daily motivational quotes designed to boost their confidence and commitment. The app also tracks user progress, providing a history of performance improvements and goals achieved.

Challenges

Developing ProFormAI presented several unique challenges:

Video Recording & Analysis: Implementing a video recording feature that supports real-time analysis while maintaining accuracy and performance was a significant technical hurdle. Ensuring compatibility across devices, maintaining low-latency processing, and optimizing the AI analysis were key focus areas. Managing the performance trade-offs between real-time video processing and delivering meaningful feedback was particularly challenging.

Real-time Feedback: Designing an AI system that provides accurate, actionable feedback in real-time required extensive fine-tuning of our models. We had to balance between speed and precision to ensure that users received feedback quickly while still maintaining a high level of accuracy.

User Engagement: Keeping users motivated was another challenge. Providing detailed feedback on form correction is essential, but equally important is offering a psychologically engaging experience. We incorporated motivational elements, such as personalized quotes, to help users feel encouraged and inspired to continue their fitness journey.

Accomplishments

We’re proud of several key accomplishments that mark the success of ProFormAI:

Successfully integrating AI-powered form analysis into a real-time video recording system, enabling users to get immediate, personalized feedback on their form.

Building an intuitive and responsive user interface that not only allows users to record and upload workout videos seamlessly but also fosters an enjoyable user experience.

Implementing a motivational component that complements the technical feedback by providing users with encouraging quotes and tracking their progress over time, creating a more holistic fitness coaching environment.

What We Learned

Combining artificial intelligence and fitness coaching is a multifaceted challenge that requires a careful balance between technology and human engagement. We learned that adapting machine learning models, such as the Random Forest Classifier, to exercise movements requires a dataset rich in diverse workout forms to ensure high-quality predictions. Our AI model was trained with professional data, but we quickly realized the need for broader training sets to account for variations in body types, flexibility, and fitness levels.

Additionally, we gained insight into the psychology of user engagement. While technical feedback is essential, it’s not enough to keep users engaged. Providing an experience that balances technical feedback with motivational support is key to retaining users and helping them achieve long-term success.

What’s Next for ProFormAI

Advanced AI Feedback: We are working on enhancing the AI’s ability to provide even more specific, granular feedback by targeting individual muscle groups and focusing on a wider range of exercises. This will allow users to receive tailored advice on how to engage specific muscles more effectively during their workouts.

Interactive Workouts: In the future, users will be able to set personalized workout plans that adapt based on their progress. The app will offer AI-guided coaching during real-time workouts, offering corrections on form as the user performs each exercise.

Community Engagement: We plan to introduce social features, such as workout challenges, leaderboards, and the ability to share progress with friends or a community of fitness enthusiasts. These features will help users stay connected and motivated, driving engagement and accountability.

Built With

• api
• clustering
• flask
• javascript
• python
• react
• sci-kit
• sklearn