Abstract
The increasingly aging population will pose a severe burden to the health services. Falls are a major health risk that diminishes the quality of life among the elderly people and increases the health services cost. Reliable fall detection and notification is essential to improve the post-fall medical outcome which is largely dependent upon the response and rescue time. In this paper, we analyze mobile phones as a platform for developing a fall detection system. The feasibility of such platform is assessed by running an acceleration based fall detection algorithm on the phone. The algorithm was implemented for the Android OS and tested on several HTC models, which included a MEMS accelerometer. Extensive simulations of fall events as well as activities of daily life were conducted on a lab environment to evaluate the system performance. Experimental results of our system, which we still consider as work in progress, are encouraging making us optimistic regarding the feasibility of a highly reliable phone-based fall detector.
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References
Masud, T., Morris, R.: Epidemiology of falls. Epidemiology of falls Age 30 (2001)
Tinetti, M.E., Doucette, J.T., Claus, E.B.: The contribution of predisposing and situational risk factors to serious fall injuries. Journal of the American Geriatrics Society 43 (1995)
Bezon, J., Echevarria, K.H., Smith, G.B.: Nursing outcome indicator: preventing falls for elderly people. Outcomes Management for Nursing Practice 3 (1999)
United Nations.: World Population Prospects. The 2004 Revision: Economic & Social Affairs (2005)
Aminian, K., Najafi, B.: Capturing human motion using body-fixed sensors: outdoor measurement and clinical applications. Computer Animation and Virtual Worlds 15 (2004)
Doughty, K., Lewis, R., McIntosh, A.: The design of a practical and reliable fall detector for community and institutional telecare. J. Telemed. Telecare (2000)
Wu, G.: Distinguishing fall activities from normal activities by velocity characteristics. Journal of Biomechanics 33 (2000)
Bourke, A.K., O’Donovan, K.J., Olaighin, G.: The identification of vertical velocity profiles using an inertial sensor to investigate pre-impact detection of falls. Med. Eng. Phys. (2008)
http://www.obsmedical.com/products/telecare-assisted-living/vivatec-nurse-call-system (accessed October 27, 2010)
Porteus, J., Brownsell, S.: Using telecare: exploring technologies for independent living for older people. Anchor Trust, Kidlington (2000)
Lindemann, U., Hock, A., Stuber, M., Keck, W., Becker, C.: Evaluation of a fall detector based on accelerometers: A pilot study. Medical & Biological Engineering & Computing 43 (2005)
Zhang, T.: Fall detection by embedding an accelerometer in cellphone and using KFD algorithm. International Journal of Computer Science and Network Security (2006)
Jiangpeng, D., Xiaole, B., Zhimin, Y., Zhaohui, S., Dong, X.: PerFallD: A pervasive fall detection system using mobile phones. In: 8th IEEE International Conference on Pervasive Computing and Communications Workshops, PERCOM Workshops (2010)
Noury, N.: Fall detection - Principles and Methods. In: 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (2007)
Noury, N., Rumeau, P., Bourke, A.K., Laighin, G., Lundy, J.E.: A proposal for the classification and evaluation of fall detectors. In: IRBM, vol. 29 (2008)
Garret, B.: An accelerometer Based Fall Detector: Development, Experimentation, and Analysis. Report (2005)
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© 2011 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Silva, M., Teixeira, P.M., Abrantes, F., Sousa, F. (2011). Design and Evaluation of a Fall Detection Algorithm on Mobile Phone Platform. In: Gabrielli, S., Elias, D., Kahol, K. (eds) Ambient Media and Systems. AMBI-SYS 2011. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 70. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23902-1_4
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DOI: https://doi.org/10.1007/978-3-642-23902-1_4
Publisher Name: Springer, Berlin, Heidelberg
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