Human Body Posture Correction System

What is it about?

With the development of technology and the progress of life, more and more people, regardless of entertainment, learning, or work, cannot do without computer desks and cannot put down their mobile phones. Due to prolonged sitting and often neglecting the importance of posture, incorrect posture can often lead to health problems such as hunchback, lumbar muscle strain, and shoulder and neck pain over time. To address this issue, we designed a computer vision-based human body posture detection system. The system utilizes YOLOv8 technology to accurately locate key points of the human body skeleton, and then analyzes the coordinate positions and depth information of these key points to establish a criterion for distinguishing different postures. With the assistance of an SVM classifier, the system achieves an average recognition rate of 95%. Finally, we successfully deployed the posture detection system on Raspberry Pi hardware and conducted extensive testing. The test results demonstrate that the system can effectively detect various postures and provide real-time reminders to users to correct poor posture, demonstrating good practicality and stability.

Featured Image

Why is it important?

The article titled "Computer Vision-Based Human Body Posture Correction System" focuses on developing a system to detect and correct poor posture using computer vision and deep learning techniques. It utilizes YOLOv8 technology to locate key points of the human skeleton and uses an SVM classifier for posture recognition, achieving a 95% recognition rate. The system is implemented on Raspberry Pi, showcasing practical applications in real-time posture correction, which is relevant for reducing health issues associated with prolonged poor posture. **Importance:** 1. **Health Improvement**: Addresses common health problems due to poor posture. 2. **Technology Application**: Demonstrates the use of computer vision and AI in everyday life. 3. **Scalability**: The deployment on Raspberry Pi indicates potential for widespread use. For more details, you can read the full article [here](https://journals.viserdata.com/index.php/mes/article/view/13221).