Fall Detection for Elderly Persons Using Android-Based Platform

Since fall event has become the most common accident occurred among elderly persons, the development of fall detection system has received much attention in recent years. With the help of such a system, elderly persons can be delivered to a hospital to receive timely medical care. This study aims to implement a fall detection system by using an Android-based watch (the WIMM one) equipped with a tri-axial gravity accelerometer. Six young persons (3 males and 3 females) were invited to conduct the experiments. By simultaneously considering the detections for linear and non-linear movements, the proposed system achieves an accuracy of 92.5%, which is an improvement of 12% as compared to the previous scheme.

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