Posture Correction Device Based on IMU Sensors and CNN

In our daily lives, good posture is important to prevent complications and promote good health. This paper introduces an innovative approach that integrates wearable technology with Convolutional Neural Networks (CNNs) to address the general issue of body posture. The proposed system comprises a lightweight wearable device embedded with sensors, continuously monitoring and capturing real-time posture data. Leveraging deep learning algorithms, a powerful CNN processes this data to accurately classify and identify various posture patterns. Unlike traditional methods, our approach offers personalized and immediate feedback through an intuitive mobile app. Users receive real-time posture assessments, visualizations, and corrective recommendations, empowering them to proactively improve their posture habits. This not only enhances posture correction but also fosters a sustainable approach to musculoskeletal health. The proposed method contributes to a more proactive approach to preventive healthcare, significantly improving musculoskeletal health and enhancing the quality of life.