TY - JFULL AU - S. Sowmyayani and P. Arockia Jansi Rani PY - 2019/4/ TI - An Efficient Fall Detection Method for Elderly Care System T2 - International Journal of Computer and Information Engineering SP - 172 EP - 177 VL - 13 SN - 1307-6892 UR - https://publications.waset.org/pdf/10010194 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 147, 2019 N2 - Fall detection is one of the challenging problems in elderly care system. The objective of this paper is to identify falls in elderly care system. In this paper, an efficient fall detection method is proposed to identify falls using correlation factor and Motion History Image (MHI). The proposed method is tested on URF (University of Rzeszow Fall detection) dataset and evaluated with some efficient measures like sensitivity, specificity, precision and classification accuracy. It is compared with other recent methods. The experimental results substantially proved that the proposed method achieves 1.5% higher sensitivity when compared to other methods. ER -