Title:
Data fusion of ambient technologies to examine relationships between activity and mild cognitive impairment

dc.contributor.advisor Clifford, Gari D.
dc.contributor.author Zelko, Jacob S.
dc.contributor.committeeMember Mynatt, Beth
dc.contributor.department Biomedical Engineering (Joint GT/Emory Department)
dc.contributor.department Biomedical Engineering (Joint GT/Emory Department)
dc.date.accessioned 2020-11-09T17:00:38Z
dc.date.available 2020-11-09T17:00:38Z
dc.date.created 2020-05
dc.date.issued 2020-05
dc.date.submitted May 2020
dc.date.updated 2020-11-09T17:00:38Z
dc.description.abstract Mild Cognitive Impairment (MCI) is a disorder that affects millions of elderly individuals across the world. Common symptoms of the condition are decreases in memory function, impaired motor control which can cause regularly occurring states of confusion. Arising from this disorder is the serious concern about how best to support those afflicted by MCI in continuing to live fulfilling, independent lives while protecting them from hazards that may arise from their MCI. Of particular interest is investigating movement patterns people with MCI exhibit while pertaining tasks or daily routines. Repetitive movement throughout the same areas of a house -- such as going from a bathroom, to kitchen, to bedroom in a cyclic fashion -- may indicate increasing severity of MCI. Though there is no known cure or prevention for MCI, identifying if one's condition is getting more severe is imperative to improving quality of life for these individuals. In this thesis, methods of low-cost location tracking were explored. A low-cost location tracking system was created and detailed. The system implemented Bluetooth technologies for identifying individuals. For receivers, devices such as Raspberry Pi computers were used to record movement patterns of individuals as they moved around an environment. Simulated scenarios were developed used to create algorithms to determine someone's location in real time.
dc.description.degree Undergraduate
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/63888
dc.language.iso en_US
dc.publisher Georgia Institute of Technology
dc.subject Data fusion
dc.subject Ubiquitous Computing
dc.subject Localization
dc.subject Mild Cognitive Impairment
dc.subject Biomedical Informatics
dc.title Data fusion of ambient technologies to examine relationships between activity and mild cognitive impairment
dc.type Text
dc.type.genre Undergraduate Thesis
dspace.entity.type Publication
local.contributor.advisor Clifford, Gari D.
local.contributor.corporatename Wallace H. Coulter Department of Biomedical Engineering
local.contributor.corporatename Undergraduate Research Opportunities Program
local.contributor.corporatename College of Engineering
local.relation.ispartofseries Undergraduate Research Option Theses
relation.isAdvisorOfPublication 9f058f41-55cb-4eb6-baac-b5b5526e280b
relation.isOrgUnitOfPublication da59be3c-3d0a-41da-91b9-ebe2ecc83b66
relation.isOrgUnitOfPublication 0db885f5-939b-4de1-807b-f2ec73714200
relation.isOrgUnitOfPublication 7c022d60-21d5-497c-b552-95e489a06569
relation.isSeriesOfPublication e1a827bd-cf25-4b83-ba24-70848b7036ac
thesis.degree.level Undergraduate
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
ZELKO-UNDERGRADUATERESEARCHOPTIONTHESIS-2020.pdf
Size:
4.09 MB
Format:
Adobe Portable Document Format
Description:
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
LICENSE.txt
Size:
3.86 KB
Format:
Plain Text
Description: