Thu Dau Mot University Journal of Science


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1 papers


Most of the indoor accidents are related with fall down. Many medical studies are point out that key factor for keeping patient’s life is fast response of monitoring system. In modern life, peoples are isolated with neighbor, especially in living quarters. Therefore many solutions are developed for falling down monitoring that base on wearable sensors. These methods require of an expensive sensors system with electric power supplier and telecommunication devices. In context of patients with disease and weak status, patients are trend to remove sensor system. This issue requires to find out another approach so that sensors system will not be needed. We study the fall detection by monitoring camera. For increase the accuracy, we proposed a simple and effective method to extract features of abnormal activities. By tracking the magnitude of entropy and its distribution, our fall detection model has a capability of differentiating falls from other activities

Publication Information

Publisher

Thu Dau Mot University, Viet Nam

Editor-in-Chief

Assoc. Prof. Nguyen Van Hiep
Thu Dau Mot University

Editorial Board

Assoc. Prof. Le Tuan Anh
Thu Dau Mot University
PhD. Nguyen Quoc Cuong
Thu Dau Mot University

PhD. Doan Ngoc Xuan
Thu Dau Mot University
PhD. Nguyen Khoa Truong An
Thu Dau Mot University

Assoc. Prof. Nguyen Thanh Binh
Thu Dau Mot University
PhD. Le Thi Thuy Dung
Thu Dau Mot University

PhD. Ngo Hong Diep
Thu Dau Mot University
PhD. Nguyen Duc Dat Duc
Ho Chi Minh City University of Industry and Trade

Assoc. Prof. Nguyen Van Duc
Animal Husbandry Association of Vietnam
PhD. Nguyen Thi Nhat Hang
Department of Education and Training of Binh Duong Province

PhD. Nguyen Thi Cam Le
Vietnam Aviation Academy
PhD. Trần Hạnh Minh Phương
Thu Dau Mot University

M.A. Pham Van Thinh
Thu Dau Mot University
PhD. Nguyen Thi Lien Thuong
Thu Dau Mot University

Prof. Le Quang Tri
Can Tho University
Prof. Banh Quoc Tuan
Thu Dau Mot University