dc.contributor.advisor | Skubic, Marjorie | eng |
dc.contributor.author | Moore, Michael James, 1983- | eng |
dc.date.issued | 2011 | eng |
dc.date.submitted | 2011 Spring | eng |
dc.description | The 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.description | Title from PDF of title page (University of Missouri--Columbia, viewed on July 22, 2011). | eng |
dc.description | Thesis advisor: Marjorie Skubic | eng |
dc.description | Includes bibliographical references. | eng |
dc.description | M.S. University of Missouri--Columbia 2011. | eng |
dc.description.abstract | The 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.extent | xiv, 120 pages | eng |
dc.identifier.uri | http://hdl.handle.net/10355/11498 | |
dc.language | English | eng |
dc.publisher | University of Missouri--Columbia | eng |
dc.relation.ispartofcommunity | University of Missouri-Columbia. Graduate School. Theses and Dissertations. Theses. 2011Theses | eng |
dc.rights | OpenAccess. | eng |
dc.rights.license | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License. | |
dc.subject | Parzen windowrelevance vector machine | eng |
dc.subject.lcsh | Infrared detectors -- Design and construction | eng |
dc.subject.lcsh | Fuzzy algorithms | eng |
dc.subject.lcsh | Personal emergency response systems | eng |
dc.subject.lcsh | Falls (Accidents) -- Mathematical models | eng |
dc.subject.lcsh | Patient monitoring | eng |
dc.title | PIR sensing array for fall detection | eng |
dc.type | Thesis | eng |
thesis.degree.discipline | Computer science (MU) | eng |
thesis.degree.grantor | University of Missouri--Columbia | eng |
thesis.degree.level | Masters | eng |
thesis.degree.name | M.S. | eng |