Real-time Posture Correction System in sitting using Deep Learning Techniques

In today's workplace, desk employees often spend long hours sitting in front of computers, leading to issues such as poor posture, back pain, neck strain, and other musculoskeletal problems. This research presents a solution using wearable devices and computer vision technology to tackle these health concerns. The system monitors the user's body position in real-time by analyzing images captured by the wearable device. It calculates body angles and relevant data to evaluate posture and offers corrective feedback when poor posture is detected. Maintaining good posture is important not only for physical well-being but also for enhancing productivity. Recognizing this, researchers and developers are creating technological solutions to help desk workers develop healthier posture habits throughout the workday. This paper introduces a system designed to promote better posture using computer vision. The camera capture real-time images of the user, and the system uses algorithms to identify key body points and calculate posture angles. If improper posture is identified, the system provides the user with guidance to make adjustments, helping prevent posture-related health issues. This technology offers a practical approach to reducing the physical strain associated with prolonged sitting, benefiting both individual health and workplace efficiency.