Effective Falls Detection Method Using Two Tri-Axial Accelerometers

Article Preview

Abstract:

Falls detection systems have been developed in recent years because falls are detrimental events that can have a devastating effect on health of the elderly population. Current fall detecting methods mainly employ accelerometer to discriminate falls from activities of daily living (ADL). However, this makes it difficult to distinguish real falls from certain fall-like activities such as jogging and jumping. In this paper, an accurate fall detection system was implemented using two tri-axial accelerometers. By attaching the accelerometers on the chest and the abdomen, our system can effectively differentiate between falls and non-fall events.The Diff_Z and Sum_diff_Z parameter resulted in falls detection rate of 100%, respectively.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

854-860

Citation:

Online since:

January 2013

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Elderly Statistics Press Release, 2009, Blreau of Statistics.

Google Scholar

[2] D. W. Kang, J. S. Choi, J. W. Lee, S. C. Chung, S. J. Park, and G. R Tack: Real-time elderly activity monitoring system based on a tri-axial accelerometer, Disability and Rehabilitation Assistive Technology, Vol. 5, No 4, pp.247-253, (2010).

DOI: 10.3109/17483101003718112

Google Scholar

[3] Sophie Turgeon Londei, Jacqueline Rousseau, Francine Ducharme, Alain St-Arnaud, Jean Meunier, Jocelyne Saint-Arnaud and Francine Giroux: An intelligent videomonitoring system for fall detection at home: perceptions of elderly people, Journal of Telemedicine and Telecare, Vol. 15 No. 8, (2009).

DOI: 10.1258/jtt.2009.090107

Google Scholar

[4] Caroline Rougier, Jean Meunier, Alain St-Arnaud, and Jacqueline Rousseau: Robust Video Surveillance for Fall Detection Based on Human Shape Deformation, IEEE transactions on circuits and systems for video technology, Vol. 21, No. 5, (2011).

DOI: 10.1109/tcsvt.2011.2129370

Google Scholar

[5] Toreyin, B.U., Y. Dedeoglu, and A.E. Cetin: HMM Based falling Person Detection Using Both Audio and Video, Lecture Notes in Computer Notes in Computer Sciences, (2005), pp.211-221.

DOI: 10.1109/siu.2006.1659753

Google Scholar

[6] Luo. S, and Q. Hu: A Dynamic Motion Pattern Analysis Approach to Fall Detection, IEEE International Workshop on Biomedical Circuit & Systems, (2004), p. s2. 1_5-S2. 1_8.

DOI: 10.1109/biocas.2004.1454088

Google Scholar

[7] Q. Li, J.A. Stankovic, M. A. Hanson, A. T. Barth, J. Lach, and G. Zhou: Accurate, Fast, Fall Detection Using Gyroscope and Accelerometer-Derived Posture Information, 2009 Sixth international Workshop on Wearable and Implantable Body Sensor Networks, (2009).

DOI: 10.1109/bsn.2009.46

Google Scholar

[8] M. Kangas, I Vikman, J. Wiklander, P. Lindgren, L. Nyberg, T. Jamsa: Sensitivity and specificity of fall detection in people aged 40 years and over, Gait & Posture, Vol. 29, (2009), pp.571-574.

DOI: 10.1016/j.gaitpost.2008.12.008

Google Scholar

[9] M. Kangas , A. Konttila, P. Lindgren, I. Winblad, and T. Jamsa: Comparison of low-complexity fall detection algorithms for body attached accelerometers, Gait & Posture, Vol. 28, (2008), p.285–291.

DOI: 10.1016/j.gaitpost.2008.01.003

Google Scholar

[10] M. N. Nyan, Francis E. H. TAY, M. Manimaran, K. H. W. Seah: Garment-based detection of falls and activities of daily living using 3-axis MEMS accelerometer, Journal of Physics, Conference Series, Vol 34, (2006), p.1059–1067.

DOI: 10.1088/1742-6596/34/1/175

Google Scholar

[11] B. Najafi, K. Aminian, A. Paraschiv-Ionescu, F. Loew, C.J. Bula, P. Robert: Ambulatory System for Human Motion Analysis Using a Kinematic Sensor Monitoring of Daily Physical Activity in the Elderly, IEEE Trans. on biomedical engineering, Vol. 50, No. 6, (2003).

DOI: 10.1109/tbme.2003.812189

Google Scholar

[12] B. R. Connell, S. L. Wolf, Environmental and Behavioral Circumstances Associated With Falls at Home Among Healthy Elderly Individuals, Archives of Physical Medicine and Rehabilitation, Vol. 78, pp.179-186, (1977).

DOI: 10.1016/s0003-9993(97)90261-6

Google Scholar