[-] Show simple item record

dc.contributor.advisorSkubic, Margeeng
dc.contributor.authorEchebiri, Chinonyeeng
dc.date.issued2013eng
dc.date.submitted2013 Springeng
dc.descriptionTitle from PDF of title page (University of Missouri--Columbia, viewed on September 13, 2013).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. Marjorie Skubiceng
dc.descriptionIncludes bibliographical references.eng
dc.descriptionM.S. University of Missouri--Columbia 2013.eng
dc.descriptionDissertations, Academic -- University of Missouri--Columbia -- Computer engineering.eng
dc.description"May 2013"eng
dc.description.abstract[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] In this study, we examine the relative amplitude - a circadian rhythm measure, as a potential feature for early illness detection. We used data collected from sensor networks to analyze the daily activity level and sleep duration of the subjects. Using algorithms designed in earlier work, the data was preprocessed to remove unwanted data such as when a subject has a visitor, and to identify when the subject is away from home so as to compensate for lack of data for that duration. Using results from earlier work as a source of ground truth for separating normal days from abnormal days, various classification methods were investigated to separate the daily relative amplitude values into normal and abnormal days but the relative amplitude data appeared to be inseparable. A fuzzy inference system was then introduced with the maximum ten-hour activity level, time-home-alone, time-in-bed, restlessness, and relative amplitude as inputs. Although the fuzzy system identified some days as abnormal, they did not match the results obtained in the earlier work. Future work could include changing the activity level value that was substituted for the times a subject is away from home, and the fuzzy rules used could also be modified and made more robust.eng
dc.format.extentvii, 58 pageseng
dc.identifier.urihttp://hdl.handle.net/10355/38535
dc.languageEnglisheng
dc.publisherUniversity of Missouri--Columbiaeng
dc.relation.ispartofcollection2013 UM restricted theses (MU)eng
dc.relation.ispartofcollectionUniversity of Missouri--Columbia. Graduate School. Theses and Dissertationseng
dc.relation.ispartofcommunityUniversity of Missouri-Columbia. Graduate School. Theses and Dissertations. Theses. 2013 Theseseng
dc.rightsAccess is limited to the campuses of the University of Missouri.eng
dc.source.originalSubmitted by the University of Missouri--Columbia Graduate Schooleng
dc.subjectearly illness detectioneng
dc.subjectaging in placeeng
dc.subjecteldercareeng
dc.subjectcircadian rhythmeng
dc.titleInvestigation of the relative amplitude method in detecting early illnesseng
dc.typeThesiseng
thesis.degree.disciplineComputer engineering (MU)eng
thesis.degree.grantorUniversity of Missouri--Columbiaeng
thesis.degree.levelMasterseng
thesis.degree.nameM.S.eng


Files in this item

[PDF]
[PDF]
[PDF]

This item appears in the following Collection(s)

[-] Show simple item record