An extension of the previous 'Fitness-AI-Coach': a complete web application with real-time exercise recognition and counting. The exercise recognition model achieves 99% accuracy on the test set and 95% and 90% on two additional external datasets. || Give a star ⭐ to the repository if it was useful. Thank you! 😊

This repository is currently used for development of Bramson the AI Motivational Gym Buddy.

This project is to be able to classify any pose into a class by being able to process the landmarks or keypoints in the image.

A Computer Vision Project for the AAI3001 module

This repository presents the implementation of our collaborative project between UPenn/Orthopaedics, UDel/Physical Therapy, and CMU/Engineering on exercise prediction.

Machine learning project for automatic barbell exercise classification using accelerometer and gyroscope sensor data from wearable devices. Features comprehensive signal processing, feature engineering, and multi-class classification to recognize 5 exercise types with intensity variations.