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ORCID
https://orcid.org/0000-0002-2906-0133
Access Type
Open Access Thesis
Document Type
thesis
Degree Program
Electrical & Computer Engineering
Degree Type
Master of Science in Electrical and Computer Engineering (M.S.E.C.E.)
Year Degree Awarded
2021
Month Degree Awarded
September
Abstract
Technology development in the sub-field of older adult care has always been on the back-burner compared to other healthcare areas. But with increasing life expectancy, this is poised to change. With the increasing older adult population, the current older adult care facilities and personnel are struggling to keep up with demand. Research conducted in the Netherlands [1] found 33,000 older adults were awaiting admission into a home for the elderly showing that demand far exceeds availability. This huge demand for older adult care has resulted in a decrease in the quality of care being provided. A recent study involving older adults aged 65 and above [2] compared the quality of care given to older adults in nursing homes in the UK and found it to be inadequate. While it is true that giant strides have been made in the field of personal health and fitness [3], we have to acknowledge that these technologies have not found widespread adoption in the elderly communities for a number of reasons which include lack of education, cognitive impediments, low-income and techno-phobia [4]. We believe that older adult care technologies should be approached from a different perspective in order to maximize outcomes. Inventions in the health care space are a moving target and a significant degree of technical aptitude and interest is required to keep up with these changes. My research work will be focused on developing a distributed system infrastructure that will enable large-scale monitoring of vital signals and early detection of emergency situations in nursing homes and assisted living communities. This new approach will increase automation in nursing homes leading to a reduction in running cost and an increase in capacity
DOI
https://doi.org/10.7275/24314898.0
First Advisor
Yeonsik Noh
Second Advisor
Erin Lamoureux
Third Advisor
Jeremy Gummeson
Fourth Advisor
Micheal Zink
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License
Recommended Citation
David, Uchechukwu Gabriel, "A Cloud Infrastructure for Large Scale Health Monitoring in Older Adult Care Facilities" (2021). Masters Theses. 1148.
https://doi.org/10.7275/24314898.0
https://scholarworks.umass.edu/masters_theses_2/1148
Included in
Computer Engineering Commons, Electrical and Computer Engineering Commons, Nursing Commons