Activities of daily living as a functional assessment predictor in older adults: a systematic review with focus on architecture in connected health

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dc.contributor.authorAlani, Adeshina
dc.contributor.supervisorWeber, Jens
dc.contributor.supervisorPrice, Morgan
dc.date.accessioned2019-12-03T19:17:54Z
dc.date.available2019-12-03T19:17:54Z
dc.date.copyright2019en_US
dc.date.issued2019-12-03
dc.degree.departmentDepartment of Computer Science
dc.degree.levelMaster of Science M.Sc.en_US
dc.description.abstractBackground: Functional Assessment (FA) in older adults is an important measure of their health status. FA using Activities of Daily Living (ADL) is a strong predictor of health outcomes, especially as we age. With the development of increasingly-connected health, we have a new opportunity for more robust and improved FA. Objective: The objective of this thesis is to collate and discuss published evidence on FA predictors and how the FA predictors can be collected using the paradigm of Connected Health (CH) architectures through an industrial case study in CHAPTER 5: INDUSTRIAL CASE STUDY. Methods: The method is to do two Systematic Literature Reviews (SLRs). The two SLRs were undertaken with Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement (PRISMA) and Parsifal, an online tool for SLR. This thesis catalogs various FA and state-of-the-art Software Engineering Architectural Tactics and Styles (SEATS) used within Connected Health (CH) that focus on ADL. The results of the cataloged information were used in the industrial case study where some of the FA predictors were automated. Articles obtained from the data source during the SLRs were filtered based on the titles, abstracts, full-text provision, English language literature, including age, which must be sixty-five years and above. Another reviewer was also included in this study, while all the defined inclusion and exclusion criteria detailed in this thesis were applied. Information about FA via ADL were extracted from the articles with further extraction on the SEATS used for computer-supported FA during the industrial case study. Data Source: During the SLRs processes, database searched included PubMed, EBSCOhost, Engineering Village, IEEE Xplore Digital Library, and ScienceDirect. The conducted search contains both controlled terms called Medical Subject Headings(MeSH) such as activities of daily living and search strings such as functional assessment, older adults, geriatrics, seniors, elderly care, and aging. Results: From four hundred and ninety-five initial abstracts and titles, nineteen full-text journal articles were included in the final review for the SLR on FA predictors. Six full-text journal articles were obtained from the SLR on CH architectures after reading its 449 titles and abstracts. In the SLR on FA predictors, predictor metrics for FA via ADL were extracted from each of the articles. Gait speed, sleep quality, and movement activities were assessed as ADL predictor metrics for FA in older adults. Other FA predictors published involved self-reported metric scale measurement using Barthel-20 scale and performance-based scale through Timed-UP and Go test. This thesis reviewed each metric for sleep quality and movement activities. In the SLR on CH architectures, quick response of ADL and resource efficiency such as sensors were some of the major tactics related to performance in Software Engineering (SE) quality in CH, while confidentiality and integrity of FA measures related to security in SE quality in CH was another major concern. Conclusion: Having conducted the two SLRs, a wide range of measures were used for FA in older adults, including consideration on the SEATS used for computer-supported FA. Overall, these FA measures and SEATS provide inexpensive and easy-to-implement FA. The diversity of the FA measures and SEATS contributes towards the development of computer-supported FA. However, future work is needed to consider the result of this study as an open-source computer-supported FA tool, and such tool should also be evaluated and verified through direct examination with older adults.en_US
dc.description.scholarlevelGraduateen_US
dc.identifier.urihttp://hdl.handle.net/1828/11346
dc.languageEnglisheng
dc.language.isoenen_US
dc.rightsAvailable to the World Wide Weben_US
dc.subjectGeriatricen_US
dc.subjectAgingen_US
dc.subjectcomputer-supported FAen_US
dc.subjectFunctional assessmenten_US
dc.subjectActivities of daily livingen_US
dc.subjectOlder adultsen_US
dc.subjectConnected healthen_US
dc.subjectArchitectural styleen_US
dc.subjectArchitectural tacticsen_US
dc.titleActivities of daily living as a functional assessment predictor in older adults: a systematic review with focus on architecture in connected healthen_US
dc.typeThesisen_US

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