🧘 Zen Posture

Tracks submitted: Lifestyle & Health, Best Use of MongoDB Atlas, Best Use of AI powered by Reach Capital

📌 Inspiration

In today's age, many people spend countless hours in front of computers, especially in computer science, leading to poor posture and potential health issues. We recognized the need for a solution that actively helps users maintain good posture while working, studying, or browsing online. This inspired us to create Zen Posture, a desktop application that serves as your personal posture companion.

💡 What It Does

Zen Posture is an intelligent desktop application that uses real-time posture detection to help users maintain healthy sitting positions throughout their day. The application features include:

• ✅ Real-time posture monitoring – Utilizes webcam input and TensorFlow to detect poor posture.
• ✅ Scheduled exercises – Guides users through exercises with reminders to prevent muscle strain.
• ✅ Detailed analytics – Tracks posture and improvement over time.

🛠 How We Built It

We developed Zen Posture using a modern tech stack:

• 🖥 Electron.js for seamless desktop integration.
• 🎨 React for the front-end UI.
• 🛢 MongoDB Atlas to facilitate smooth interaction between the front end and back end.
• 🤖 TensorFlow AI stack that trains data based on points plotted at the user's shoulders and nose.
• 🔔 Lightweight notification system to alert users when poor posture is detected, promoting better ergonomics.

🚧 Challenges We Ran Into

We faced multiple challenges, including:

• ❌ Integrating the backend, frontend, and machine learning components.
• 🎭 Designing a sleek, user-friendly interface.
• 🔍 Overcoming backend issues—initially, we didn’t use MongoDB Atlas, but we worked around it using the community version.
• 🔗 Solving compatibility issues by carefully reading integration documentation and ensuring all components worked together.

🏆 Accomplishments That We're Proud Of

• 🎨 Created a sleek, modern interface that makes posture tracking engaging.
• 📢 Implemented an efficient notification system to help users stay mindful.
• 📊 Developed a comprehensive analytics dashboard for progress tracking.
• 💻 Built a cross-platform desktop application that runs smoothly.
• 🤖 Created a machine learning model that accurately detects poor posture.
• 📏 Utilized geometry to calculate the distance between the shoulders and nose—if the user is hunched over, the distance shortens.
• 🏋️ Trained the model on hundreds of images, normalized the data, and created a posture score (1-100) based on user alignment.

📚 What We Learned

• 💻 Developing a desktop application using Electron.js.
• 📈 Implementing real-time data processing and visualization for posture tracking.
• 🎯 Using BlazePose to map body points.
• 📐 Applying geometry to detect breaks in posture.
• 🚀 Optimizing performance for continuous monitoring.
• 🎨 Designing a health-focused UI for user engagement.
• 🤝 The importance of teamwork and communication—we worked collaboratively, sharing ideas and supporting each other.

🚀 What's Next for Zen Posture

There’s so much potential for Zen Posture, and we aim to expand its capabilities:

• 🔬 Improved machine learning for more accurate posture detection.
• ⚕️ Additional health-based detection systems.
• ☁️ Cloud synchronization to track progress across multiple devices.
• 🎮 Social features—users can form groups, compete, and earn rewards based on posture improvement.

🛠 Built With

• Electron
• React
• Node.js
• JavaScript
• Chart.js
• MongoDB
• TensorFlow
• BlazePose
• Keras
• Pandas
• CSS
• HTML