A real-time fall detection system based on the acceleration sensor of smartphone

• Main Authors: Youngmin Lee, Hongjin Yeh, Ki-Hyung Kim, Okkyung Choi
• Format: Article
• Language: English
• Published: SAGE Publishing 2018-01-01
• Series: International Journal of Engineering Business Management
• Online Access: https://doi.org/10.1177/1847979017750669

Falls are a major problem for the elderly people leading to injury, disability, and even death. In this article, we propose a fall detection system that uses the acceleration sensor of a smartphone to detect a senior citizen falling in real time and to use the communication capabilities of the smartphone to notify the administrator of such an event. The proposed system conducts real-time location tracking using Google’s Map and 3D information to cope with a critical situation and to make an urgent intervention in an emergency. Since Google’s 3D mapping service can provide information on the surrounding buildings and their shapes with more precision than a 2D service or text-based service, it is possible to ensure a prompt response for senior citizens when such location information is available. To verify the validity and efficiency of this article, we measured the change in acceleration sensor value by classifying the subjects by age group and gender. As a result, we found that the signal vector magnitude value of the acceleration sensor value variation showed a great difference in daily life such as walking, running, sitting, and falling.