Health Monitoring System for Desk Workers Using Non-Contact Multi-Sensors

As society ages, the workload of desk workers is increasing, leading many to experience overwork and heightened job-related stress. However, due to busy schedules, they often neglect their health and cannot regularly undergo health checks. Consequently, many desk workers suffer from various health issues, including the risk of overwork-related death. To address these issues, existing research has explored real-time health monitoring using medical devices and cameras, but this approach is costly and raises privacy concerns. Therefore, we propose a new system that utilizes low-cost, non-contact multi-sensors to monitor the vital signs of office workers in real-time. The system employs infrared sensors to monitor body and environmental temperature, analyzes temperature images to identify sitting posture, and uses millimeter-wave sensors to track heart and respiration rates. Additionally, a multi-modal deep learning model with an attention mechanism extracts key features from these vital signs to assess individual health status and psychological stress levels. The system delivers real-time monitoring results to desk workers' devices and provides advice when potential health issues are detected, such as suggesting rest or seeking medical attention.