E-FallD: A fall detection system using android-based smartphone

With the rapid growth of the population of the elderly in the world, many countries in the world have been in the aging society. Falls are a major public health concern and one of the greatest obstacles to independent living for elder adults in terms of social services. In this paper, we present a fall detection system derived from some motion sensor via an android-based smart phone in which we utilize adaptive threshold algorithm for fall detection. Furthermore, we implement this system called E-FallD on the HTC G8 mobile phone. As demonstrated by the experimental results, E-FallD has a good detection performance and it is an efficient and smart application. In the mean time, using adaptive threshold algorithm could increase sensitivity dramatically. In a word ,our system provides a realizable, effective and portal solution to fall detection for users.

[1]  Xinguo Yu Approaches and principles of fall detection for elderly and patient , 2008, HealthCom 2008 - 10th International Conference on e-health Networking, Applications and Services.

[2]  M. Alwan,et al.  A Smart and Passive Floor-Vibration Based Fall Detector for Elderly , 2006, 2006 2nd International Conference on Information & Communication Technologies.

[3]  Rita Cucchiara,et al.  A multi‐camera vision system for fall detection and alarm generation , 2007, Expert Syst. J. Knowl. Eng..

[4]  Ilias Maglogiannis,et al.  Patient Fall Detection using Support Vector Machines , 2007, AIAI.

[5]  Frank Sposaro,et al.  iFall: An android application for fall monitoring and response , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[6]  Otto W. Witte,et al.  Falls and gait disorders in geriatric neurology , 2010, Clinical Neurology and Neurosurgery.

[7]  R. Bajcsy,et al.  Wearable Sensors for Reliable Fall Detection , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[8]  P. Phukpattaranont,et al.  Improving the accuracy of a fall detection algorithm using free fall characteristics , 2010, ECTI-CON2010: The 2010 ECTI International Confernce on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology.

[9]  Dong Xuan,et al.  PerFallD: A pervasive fall detection system using mobile phones , 2010, 2010 8th IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops).

[10]  Ming Zhang,et al.  Dynamic Fall Detection and Pace Measurement in Walking Sticks , 2007, 2007 Joint Workshop on High Confidence Medical Devices, Software, and Systems and Medical Device Plug-and-Play Interoperability (HCMDSS-MDPnP 2007).