Wearable Sensor with Artificial Intelligence for Prevention of Falling Elderly People

Falling down is among the major causes of medical problem that are faced by the elderly people. Elderly people tend to injured themselves from falling down more often especially when they are living alone. When a falling event occurred, medical attention needs to be provided immediately in order to reduce the risk of faller from getting severe injuries which may lead to death. Several technologies have been developed which some utilized webcams to monitor the activities of elderly people. However, the cost of operation and installation is expensive and only applicable for indoor environment. Some user also worried about their privacy issues. Current commercialized device required user to wear wireless emergency transmitter in form of pendant and wristband. This method will restrict the user movement and produce high false alarm due to frequent swinging and movement of the device. This project proposed a fall detection system which is cost effective and reliable to detect fall and alert nearby healthcare center or relatives for help and support. For fall detection, accelerometer and gyroscope was used to detect acceleration and body tilt angle of the faller respectively. By coupling accelerometer with gyroscope, the accuracy of the system was improved due to reducing in false positives and true negatives. False alarm was minimized due to the device’s position mounted on the upper trunk of the user’s body. Alert system in form of Short Message Service (SMS) was transmitted to the concerned authorities. Moreover, this wearable device requires less implementation cost and provides a quick response. As a result, this fall detection and alert system has the sensitivity and specificity of 95% and 90% respectively. However, the limitation of this device is unable to detect a user falling against a wall and falling end in sitting position. Recommendation for future work is to develop an interactive display which enables users to input nearby healthcare center and relative’s phone number.