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dc.contributor.advisorSkubic, Marjorieeng
dc.contributor.authorMoore, Michael James, 1983-eng
dc.date.issued2011eng
dc.date.submitted2011 Springeng
dc.descriptionThe entire thesis text is included in the research.pf file; the official abstract appears in the short.pdf file; a non-technical public abstract, appears in the public.pdf file.eng
dc.descriptionTitle from PDF of title page (University of Missouri--Columbia, viewed on July 22, 2011).eng
dc.descriptionThesis advisor: Marjorie Skubiceng
dc.descriptionIncludes bibliographical references.eng
dc.descriptionM.S. University of Missouri--Columbia 2011.eng
dc.description.abstractThe purpose of the Fuzzy PIR Fall Detection Array is to keep the elderly safe by providing a means for an immediate response to falls while still allowing them to enjoy the same independence they felt before fall detection was necessary. To accomplish this goal, a vertical array of passive infrared (PIR) motion sensors can be positioned anywhere in the home near where a fall may occur. A fall is considered to be observed by the sensor array when the sensors, first, detect motion, then, stop detecting motion in order from top to bottom. To differentiate between a legitimate fall and normal motion, pattern recognition techniques were used to observe the signals from the sensing array and classify whether a window of data was observed during a fall or a non-fall. To accomplish this goal, a Gaussian Parzen Window (GPW) and a relevance vector machine (RVM) were used with some success. This research shows that, for this application, the RVM was able to detect falls with an accuracy of about 80% to the Parzen Window's about 75%. Besides being more accurate, the RVM algorithm has a faster run time for classifying the data. The sensing array explored in this research could be a viable option as a non-wearable means for protecting the elderly in the event that they should fall in their home.eng
dc.format.extentxiv, 120 pageseng
dc.identifier.urihttp://hdl.handle.net/10355/11498
dc.languageEnglisheng
dc.publisherUniversity of Missouri--Columbiaeng
dc.relation.ispartofcommunityUniversity of Missouri-Columbia. Graduate School. Theses and Dissertations. Theses. 2011Theseseng
dc.rightsOpenAccess.eng
dc.rights.licenseThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License.
dc.subjectParzen windowrelevance vector machineeng
dc.subject.lcshInfrared detectors -- Design and constructioneng
dc.subject.lcshFuzzy algorithmseng
dc.subject.lcshPersonal emergency response systemseng
dc.subject.lcshFalls (Accidents) -- Mathematical modelseng
dc.subject.lcshPatient monitoringeng
dc.titlePIR sensing array for fall detectioneng
dc.typeThesiseng
thesis.degree.disciplineComputer science (MU)eng
thesis.degree.grantorUniversity of Missouri--Columbiaeng
thesis.degree.levelMasterseng
thesis.degree.nameM.S.eng


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