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

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Zelko, Jacob S.
Clifford, Gari D.
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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.
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Undergraduate Thesis
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