Application of a real-time motion detection system for bedridden patients using IoT technology for healthcare

Abstract

The application of real-time IoT-based movement detection for bedridden patients is essential for modern healthcare. In addition to its application in medical science, this enhances healthcare quality through precise patient monitoring. Technology enhances sustainable healthcare quality through precise and effective patient monitoring. The system has the potential to reduce caregiver workload while enabling a more efficient analysis of patient behavioral patterns. This study aims to detect real-time movements using accelerometers and Force Sensitive Resistors (FSR). Experimental results demonstrated that Z-axis acceleration (Z-Acc) significantly peaked at 12.8 m/s² during sudden movements (20-22 seconds), while Roll and Pitch angles exhibited periodic variations during normal activity. To evaluate the system’s efficacy, visual data analysis was employed to classify key movement states, including stationary positions, body turning, and bed-exit events incidents. These findings suggest that the system significantly enhances the safety and quality of life for bedridden patients.