@inproceedings{e7c7ac014b20469f9961d12e2c1ba2c9,
title = "Design and implementation of a fall detection system on a Zynq board",
abstract = "Population aging has become a worldwide problem. Fall accidents are considered as one of the major health risks, especially for elderly people. Fall detection devices are the key to distinguish a fall from daily activities, automatically alert when a fall occurred and significantly decrease the time of rescue when the monitored patient falls down. The proposed prototype is composed of a tri-axial accelerometer communicating to a Zybo board through Inter-Integrated Circuit (I2C) interface. A threshold-based algorithm has been implemented based on peaks acceleration detection and inactivity posture recognition after falling and executed as a standalone application on a Zynq Z-7010 Field Programmable Gate Array (FPGA). This first implementation using Vivado and Xilinx SDK showed prominent results in terms of power consumption and time of execution.",
keywords = "E-health, Embedded systems, Fall detection, FPGA, Tri-axial accelerometer",
author = "Sahar Abdelhedi and Mouna Baklouti and Riad Bourguiba and Jaouhar Mouine",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 13th IEEE/ACS International Conference of Computer Systems and Applications, AICCSA 2016 ; Conference date: 29-11-2016 Through 02-12-2016",
year = "2016",
month = jul,
day = "2",
doi = "10.1109/AICCSA.2016.7945775",
language = "English",
series = "Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA",
publisher = "IEEE Computer Society",
booktitle = "2016 IEEE/ACS 13th International Conference of Computer Systems and Applications, AICCSA 2016 - Proceedings",
address = "United States",
}