Fall detection of elderly through floor vibrations and sound

Dima Litvak, Yaniv Zigel, Israel Gannot

Research output: Contribution to conferencePaperpeer-review

79 Scopus citations

Abstract

Falls are very prevalent among the elderly especially in their home. The statistics show that approximately one in every three adults 65 years old or older falls each year. Almost 30% of those falls result in serious injuries. Studies have shown that the medical outcome of a fall is largely dependent upon the response and rescue time. Therefore, reliable and immediate fall detection system is important so that adequate medical support could be delivered. We have developed a unique and inexpensive solution that does not require subjects to wear anything. The solution is based on floor vibration and acoustic sensing, and uses a pattern recognition algorithm to discriminate between human or inanimate object fall events. Using the proposed system we can detect human falls with a sensitivity of 95% and specificity of 95%

Original languageEnglish
Pages4632-4635
Number of pages4
DOIs
StatePublished - 1 Jan 2008
Event30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 - Vancouver, BC, Canada
Duration: 20 Aug 200825 Aug 2008

Conference

Conference30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
Country/TerritoryCanada
CityVancouver, BC
Period20/08/0825/08/08

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