@inproceedings{d32ff18c2d4b41a5a051cadb35a15eea,
title = "Development of a two-threshold-based fall detection algorithm for elderly health monitoring",
abstract = "Population aging has become a worldwide problem. Falls are considered as the first source of disabilities among elderly people. Fall detection algorithms 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 algorithm presented in this paper uses tri-axial accelerometer outputs to discriminate between falls and daily activities. It is mainly based on a two-thresholds approach and inactivity posture recognition after falling. The algorithm showed prominent results compared to existing works and will be improved and implemented on a Zynq board for future applications.",
keywords = "e-health, embedded systems, fall detection, FPGA, tri-axial accelerometer",
author = "Sahar Abdelhedi and Riad Bourguiba and Jaouhar Mouine and Mouna Baklouti",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 10th IEEE International Conference on Research Challenges in Information Science, IEEE RCIS 2016 ; Conference date: 01-05-2016 Through 03-05-2016",
year = "2016",
month = aug,
day = "23",
doi = "10.1109/RCIS.2016.7549315",
language = "English",
series = "Proceedings - International Conference on Research Challenges in Information Science",
publisher = "IEEE Computer Society",
editor = "Jolita Ralyte and Sergio Espana and Carine Souveyet",
booktitle = "IEEE RCIS 2016 - IEEE 10th International Conference on Research Challenges in Information Science",
address = "United States",
}