A research on automatic human fall detection method based on wearable inertial force information acquisition system

Authors:
Lina Tong;Wei Chen;Quanjun Song;Yunjian Ge
Affiliations:
Institute of Intelligent Machines, Chinese Academy of Sciences and Automation Department, University of Science and Technology of China;Institute of Intelligent Machines, Chinese Academy of Sciences and Automation Department, University of Science and Technology of China;Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, China;Institute of Intelligent Machines, Chinese Academy of Sciences
Venue:
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
Year:
2009

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Abstract

Frequent and high-risk fall accidents of the elders have become a serious medical and social problem. In this paper, a wireless automatic human fall detection device based on tri-axis accelerator is designed and realized; and a novel method to distinguish fall events from other daily activities is proposed also, including multi-impact falls and rolling down falls. In the real application, the device is worn on upper trunk of human body, with the algorithm focusing on the impact during a fall and the orientation of trunk before the fall and after it. At last, experiment is performed on some typical daily activities, such as walking, stand-to-sit, stand-to-squat, fall frontward, sideways, etc, and it has shown good results in high detection rate and low positive false rate.