Posture Anomaly Detection AI System Built Using Python

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About Project

In today’s fast-paced world, maintaining physical fitness and mental well-being has become a priority for many individuals. Regular exercise is not only a well-known discipline but also a crucial factor in enhancing overall health. However, ensuring correct posture during exercise is often overlooked, leading to potential injuries and ineffective workouts. To address this issue, posture detection systems have emerged as valuable tools in the fitness industry.

Posture detection technology utilizes machine learning algorithms to identify and improper posture during specific exercises. By analyzing key body points, these systems provide feedback to users, helping them maintain proper form and maximize the benefits of their workouts. Whether it’s on a treadmill or performing squats, the application of machine learning ensures accurate posture assessment across various exercise types.

Duration

7 Days

Release date

Mar 2024

Working Hours

56 Hours

Business Challenge

While existing posture detection systems focus on general posture correction, our solution aims to tackle the specific challenge of identifying incorrect posture during different exercises. One of the primary challenges is integrating exercise type recognition into the detection process. Our system addresses this challenge by allowing users to define exercise types and set rules accordingly.

Utilizing Google Pose Landmarker library, our model accurately identifies key body points and marks incorrect posture positions. Moreover, it provides detailed explanations for why the detected posture is incorrect, enhancing user understanding and engagement.

Business Solution

This application helps users with their workout routines by providing posture detection and correction feedback. Users can personalize exercise types and rules based on their needs. The application integrates with existing fitness platforms and devices.

Technical details

At the core of our solution lies a posture analysis application utilizing Google’s Pose Landmarker library to detect key points on the body. These points are then analyzed against predefined rules for various exercises, stored in a JSON file. Through angle calculations and distance measurements between points, our system accurately identifies correct posture. In the event of incorrect posture, OpenCV library in Python is utilized to highlight problematic areas and provide visual feedback to the user.

The system is scalable and adaptable. New exercises can be integrated by adding exercise information and corresponding rules.

The application can be deployed using Docker containers on a server with an API for receiving images and exercise types for feedback.

Applied Technologies

Our Role in Client Success

Posture detection technology uses machine learning to analyze body position during exercise. This can help users improve their form and reduce the risk of injury. As the technology continues to develop, it could become a valuable tool for improving overall fitness.