Enhancing Spine Health Management: Real-Time Monitoring and Analysis with Sensor Technology

This study proposes a system to monitor spine mobility and detect pain levels using integrated force and flex sensors. By collecting real-time data, the system enables healthcare professionals to track spinal movements and provide personalized therapeutic interventions. Strategically placed sensors along the spine monitor motion and discomfort, helping identify abnormal patterns that may indicate underlying issues. Advanced machine learning algorithms analyze the parameters to determine pain onset, offering early warnings to healthcare providers. This predictive capability supports timely interventions, preventing pain escalation and enhancing patient outcomes. Additionally, the system personalizes therapy by adapting exercises to individual patient needs. Continuous monitoring of mobility and pain thresholds ensures tailored treatments, improving adherence and recovery. By combining continuous monitoring, predictive analysis, and customized therapy, this system aims to transform spinal health management. It empowers healthcare providers with actionable insights, enabling earlier interventions and improving therapeutic outcomes for patients with spinal conditions.