Patient Fall Monitoring System using Arduino and Bluetooth

Falls are one of the major causes of injury for elderly and mobility-impaired patients, which require immediate detection and intervention to avoid severe repercussions. The proposed project is a Patient Fall Monitoring System based on Arduino and Bluetooth technology for real-time fall detection and immediate caregiver notification. The system employs a MEMS sensor for continuous monitoring of patient movement by analyzing posture changes, speed, and acceleration for detecting sudden and uncontrolled falls. A threshold-based fall detection algorithm is implemented to analyze sensor data to differentiate between normal activity and true falls. Once a fall is detected, the system instantaneously sends notifications over Bluetooth to enrolled mobile devices and triggers a buzzer alarm for local alerting. Experiments showed high sensitivity to detect different types of fall events including slipping, stumbling, and sudden loss of balance. Regardless of environmental factors such as vibrations and the range constraints of Bluetooth, the system was found to be reliable in conveying emergency messages without perceivable delay. The open-source design of Arduino allows for continuous improvement, with future expansions potentially being Wi-Fi or cellular communication for increased coverage. The system improves patient safety through real-time monitoring, quick alerts, and real-time intervention.