Lightweight Wearable Fall Detection System for Elderly Using Gait Analysis

Falls among the elderly represent a critical health risk, often resulting in serious injuries, prolonged recovery, and decreased autonomy. This project addresses this issue by developing a sophisticated yet lightweight wearable fall detection system that uses advanced gait analysis to monitor and detect falls in real time. The system employs the ADXL345 accelerometer to capture detailed movement data and analyze gait patterns, distinguishing between normal activities and falls with high accuracy. Upon detecting a fall, the system immediately triggers an alert, sending a message that includes GPS location coordinates to a designated phone number. This feature ensures that emergency services or caregivers can quickly reach the individual, significantly reducing response time and improving overall safety. The wearable device is designed for comfort and ease of use, making it suitable for continuous wear by elderly individuals. It integrates seamlessly into daily life without being obtrusive, offering both functionality and user comfort. This project aims to enhance the quality of elderly care by providing a reliable, responsive, and user-friendly fall detection solution, ultimately contributing to the prevention of fall-related injuries and supporting independent living for seniors.