Wearable Device for Fall Detection Using 3-D Accelerometer
Nasiya. PM1
Section:Research Paper, Product Type: Journal Paper
Volume-06 ,
Issue-06 , Page no. 17-20, Jul-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6si6.1720
Online published on Jul 31, 2018
Copyright © Nasiya. PM . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Citation
IEEE Style Citation: Nasiya. PM, “Wearable Device for Fall Detection Using 3-D Accelerometer,” International Journal of Computer Sciences and Engineering, Vol.06, Issue.06, pp.17-20, 2018.
MLA Citation
MLA Style Citation: Nasiya. PM "Wearable Device for Fall Detection Using 3-D Accelerometer." International Journal of Computer Sciences and Engineering 06.06 (2018): 17-20.
APA Citation
APA Style Citation: Nasiya. PM, (2018). Wearable Device for Fall Detection Using 3-D Accelerometer. International Journal of Computer Sciences and Engineering, 06(06), 17-20.
BibTex Citation
BibTex Style Citation:
@article{PM_2018,
author = {Nasiya. PM},
title = {Wearable Device for Fall Detection Using 3-D Accelerometer},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2018},
volume = {06},
Issue = {06},
month = {7},
year = {2018},
issn = {2347-2693},
pages = {17-20},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=437},
doi = {https://doi.org/10.26438/ijcse/v6i6.1720}
publisher = {IJCSE, Indore, INDIA},
}
RIS Citation
RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i6.1720}
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=437
TI - Wearable Device for Fall Detection Using 3-D Accelerometer
T2 - International Journal of Computer Sciences and Engineering
AU - Nasiya. PM
PY - 2018
DA - 2018/07/31
PB - IJCSE, Indore, INDIA
SP - 17-20
IS - 06
VL - 06
SN - 2347-2693
ER -




Abstract
A fall detection device is needed to provide information to paramedics or family members when an elderly is falling. Helping for elderly falling can avoid fatal injuries or loss of life. In order for the falling device comfortably taken by the elderly, this proposed a wearable device that lightweight, using battery for power supply, and a low-energy consumption. proposed device consists of 3-dimensional accelerometer, a communication device and a microcontroller . The sensor meassures accelerations of body movements. Then, the microcontroller identifies position body and a falling from three-axis accelerations. proposed method, that has success detect 75% in fall forward and 95% in fall backward. The proposed device also has a 100% success in providing information on normal activities, such as: standing or sitting, supine, face down, left and right, while the success rate for the e-health device by cooking hack is 92%.
Key-Words / Index Term
Fall Detection, Wearable Device, 3-D Accelerometer
References
[1] M. Peden, K. McGee, and G. Sharma, “The injury chart book: a Graphical overview of the global burden of injuries”, Geneva: World Health Organization, vol. 5, 2002.
[2] K. E. Thomas, J. A. Stevens, K. Sarmiento, and M. M. Wald, “Fallrelated traumatic brain injury deaths and hospitalizations among older adultsunited states”,Journal of safety research, vol. 39, no. 3, pp. 269272,2008.
[3] Causes elderly people to fall, http : // www .agingcare .com / Articles /Fallsin-elderly-people 133953.htm, Accessed: May 18,2015.
[4] B. J. Lee, S. F. Su, and I. Rudas, “Content-independent image Processing based fall detection”, in System Science and Engineering ICSSE), 2011 International Conference on, pp. 654659, IEEE, 2011.
[5] H. W. Tzeng and M. Y. Chen,” Design of fall detection system with floor pressure and infrared image”, in System Science and Engineering (ICSSE), 2010 International Conference on, pp. 131135, IEEE, 2010.
[6] T. Zhang, J. Wang, L. Xu, and P. Liu, Fall detection by wearable sensor and one-class svm algorithm, in Intelligent Computing in Signal Processing and Pattern Recognition, pp. 858863, Springer, 2006.
[7] P. Salgado, P. Alfonso, Fall body detection algorithm based on Tri- Accelerometer sensors, in IEEE International Symposium on Computational Intelligence and Informatics, 2013.