AI-powered overhead press form analysis. Detects incorrect elbow and knee alignment in real-time to improve lifting technique and prevent injuries.
Advanced AI models analyze video input frame-by-frame, focusing on elbow flare, knee cave, and other common overhead press mistakes.
Read the full technical report (PDF)
- Real-time detection of improper elbow and knee positioning during overhead presses
- Multiple model architectures: LSTM, Custom LSTM, Feedforward
- Video upload & keypoint extraction (MediaPipe)
- Frame-level predictions for knees and elbows
- REST API endpoint for integration with frontends/mobile apps
- Training pipelines with checkpointing and metrics tracking
- Evaluation metrics (accuracy, precision, recall, F1) per joint
- Backend: Python, Flask
- Machine Learning: TensorFlow/Keras
- Computer Vision: MediaPipe, OpenCV
- Data Processing: NumPy, scikit-learn
- API: Flask + CORS
- Frontend: React, ChartJS, Tailwind