Exercise Form Correction Using Machine Learning

Introduction

Explore FitAssist, the innovative platform that merges the potential of Computer Vision, Machine Learning, and Image Processing to revolutionize your fitness journey. With real-time exercise classification and form correction, FitAssist ensures that you exercise safely and effectively while offering personalized feedback and a vibrant fitness community.

Problem Statement

Traditional fitness routines lack real-time feedback on exercise form, leading to a higher risk of injuries and suboptimal results. People often struggle with maintaining proper exercise technique, especially when working out alone. The need for personalized guidance during workouts is crucial, and existing solutions fall short in delivering accurate and immediate assistance.

Challenges

Real-time Analysis: Providing real-time analysis of exercise form required the development of advanced Computer Vision and Machine Learning algorithms capable of processing video footage on the fly.

Precise Pose Estimation: Accurately tracking body joints and movement was challenging, especially when considering different exercise types and body positions.

Video Classification: Automatically recognizing and categorizing exercises needed robust video classification models.

Image Processing: Overcoming suboptimal lighting conditions and crowded workout spaces to ensure accurate data extraction.

Angle Computation: Calculating precise angles and joint positions through computational geometry.

Social Interaction: Creating a community platform for users to share their workouts and receive constructive feedback was a complex endeavor.

Solution

FitAssist addresses these challenges by combining the latest technologies and techniques:

Computer Vision & Machine Learning: The platform employs cutting-edge Computer Vision and Machine Learning to analyze exercise form in real time.

Pose Estimation: Pose Estimation algorithms accurately identify and track body joints, ensuring precise form analysis.

Video Classification: Automated recognition and categorization of exercises provide users with personalized feedback.

Image Processing: Image Processing enhances video quality and ensures accurate data extraction, even in challenging conditions.

Angle Computation: FitAssist calculates crucial angles and joint positions through computational geometry.

Real-time Feedback: Users receive immediate feedback, helping them correct their form and reduce injury risk.

Progress Tracking: A progress tracking feature allows users to monitor their exercise form and performance over time.

Social Interaction: FitAssist's community platform enables users to share their workouts and receive constructive feedback from fellow fitness enthusiasts and professionals.