Precision Healing: Transforming Spinal Wellness with Neural Precision and K-Fold Cross-Validation

Maintaining a good health alongside work seems hectic and also a concern if not taken care of. We always want things happen automatically and if we can integrate the technologies we work on to maintain our health, it would do wonders. In this work, we focus on developing a prototype of a smart chair integrated with intelligent technologies to help employees take care of their spinal health alongside doing their work. The intelligent identifier incorporates machine learning algorithms that continually adapt and improve based on user feedback and data analysis. The adaptive learning feature enhances the system's accuracy in recognizing subtle changes in posture and provides personalized recommendations to users for optimizing their sitting habits. Moreover, the proposed system integrates with mobile applications and wearable devices, allowing users to track their posture and health metrics seamlessly. This integration enhances user engagement and enables a holistic approach to wellness management, encompassing both posture monitoring and overall health tracking. For healthcare professionals, the proposed system offers comprehensive analytics tools that provide insights into trends and patterns in patients' sitting behaviors. This data-driven approach enables proactive interventions, early detection of potential health issues, and better management of chronic conditions related to posture and sitting habits. The proposed model is developed with the use of sensors and internet of things, giving precision in sensing the posture and correcting the postures. Furthermore, our intelligent identifier is designed with high privacy and data security, ensuring that sensitive user information is protected at all times. This commitment to privacy and security enhances user trust and confidence in the system, leading to greater adoption and long-term benefits for individuals and healthcare providers alike.