Abstract: In this paper, we describe our work on developing an automatic fall detection technique using smart phone. Fall is detected based on analyzing acceleration patterns generated during various activities. An additional long lie detection algorithm is used to improve fall detection rate while keeping false positive rate at an acceptable value. An application prototype is implemented on Android operating system and is used to evaluate the proposed technique performance. Experiment results show the potential of using this app for fall detection. However, more realistic experiment setting is needed to make this technique suitable for use in real life situations.

Tran Tri Dang, Hai Truong and Tran Khanh Dang, “Automatic Fall Detection using Smartphone Acceleration Sensor” International Journal of Advanced Computer Science and Applications(IJACSA), 7(12), 2016. http://dx.doi.org/10.14569/IJACSA.2016.071216

@article{Dang2016,
title = {Automatic Fall Detection using Smartphone Acceleration Sensor},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.071216},
url = {http://dx.doi.org/10.14569/IJACSA.2016.071216},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {12},
author = {Tran Tri Dang and Hai Truong and Tran Khanh Dang}
}