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dc.contributor.advisorPopescu, Mihail, 1962-eng
dc.contributor.authorLi, Yun, 1984-eng
dc.date.issued2009eng
dc.date.submitted2009 Falleng
dc.descriptionTitle from PDF of title page (University of Missouri--Columbia, viewed on March 10, 2010).eng
dc.descriptionThe entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file.eng
dc.descriptionThesis advisor: Dr. Mihail Popescu.eng
dc.descriptionIncludes bibliographical references.eng
dc.descriptionM.S. University of Missouri--Columbia 2009.eng
dc.descriptionDissertations, Academic -- University of Missouri--Columbia -- Electrical engineering.eng
dc.description.abstract[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] More than 1/3 of adults aged 65 and older fall each year in the US. The fall causes injures or serious health problems which have the related medical cost of $19 billion. Since many falls are not reported, this may be an indication of increasing frailty. To address the above problem we propose to develop fall detection system (FADE) that will automatically report a fall to the monitoring caregiver. As opposed to many existing fall detection systems, our system is completely unobtrusive by using microphone array rather than requiring any wearable devices. We use kinds of features (MFCC, ERSB, etc.) and classifiers ( Nearest Neighbor, Fuzzy rule system, etc.) to detect the falls and try to reduce the false alarm rate. The proposed fall detection system will leverage the existing research and expertise from the Center for Eldercare and Rehabilitation Technologies at the University of Missouri. The proposed technology will reduce the time between the fall and the medical intervention, thus increasing the rehabilitation chances.eng
dc.format.extentviii, 76 pageseng
dc.identifier.oclc558876403eng
dc.identifier.urihttps://hdl.handle.net/10355/6651
dc.identifier.urihttps://doi.org/10.32469/10355/6651eng
dc.languageEnglisheng
dc.publisherUniversity of Missouri--Columbiaeng
dc.relation.ispartof2009 MU restricted theses (MU)eng
dc.relation.ispartofcommunityUniversity of Missouri-Columbia. Graduate School. Theses and Dissertations. Theses. 2009 Theseseng
dc.rightsAccess is limited to the campus of the University of Missouri--Columbia.eng
dc.subject.lcshFalls (Accidents) in old age -- Technological innovationseng
dc.subject.lcshFalls (Accidents) in old age -- Preventioneng
dc.subject.lcshFalls (Accidents) in old age -- Safety measureseng
dc.subject.lcshDwellings -- Security measureseng
dc.titleFall detection using sound sensorseng
dc.typeThesiseng
thesis.degree.disciplineElectrical engineering (MU)eng
thesis.degree.grantorUniversity of Missouri--Columbiaeng
thesis.degree.levelMasterseng
thesis.degree.nameM.S.eng


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