<![CDATA[Stroke rehabilitation patients have a high risk of falling, requiring continuous supervision to ensure safety and support the recovery process. This research aims to design and build a mobile-based Internet of Things (IoT) system to monitor patients' fall risk in real-time. The system utilizes a wearable device integrated with an ESP32-C3 microcontroller, an Inertial Measurement Unit (IMU) MPU-6050 sensor, and a BMP280 pressure sensor to acquire patient movement and altitude data. This data is transmitted via Bluetooth Low Energy (BLE) to a mobile application to be analyzed using a fall detection algorithm. The analysis results are displayed on the application interface as a risk status, activity graphs, and alert notifications if a potential fall is detected. The resulting design demonstrates that this system is effective in assisting caregivers to comprehensively monitor the patient's condition. Through accurate and responsive monitoring, this system is expected to enhance patient safety during rehabilitation and provide useful historical data for medical personnel.]]>
Copyrights © 2025
