Title

Data Structuring in Alzheimer's

Student Classification

Sophomore

Faculty Mentor

Hilda Goins

Department

Industrial and Systems Engineering

Document Type

Poster

Publication Date

Fall 2018

Abstract

Cognitive function is defined as a person’s performance in objective tasks that require conscious mental effort. Cognitive impairment occurs when a person has trouble performing objective tasks such as remembering, learning, or concentrating. has shown that environmental factors such as heat, glare, and noise are known to be stressors of people with cognitive impairment. Behavioral and Environmental Sensing and Intervention (BESI) for caregiver empowerment is a team of ers from the engineering and medical fields tasked with understanding the environmental factors that influence agitated behaviors in People with Dementia(PWD). BESI is a cyber-human system compromising a tablet for inputs by the caregivers, sensors placed in different locations in the home, a wrist-worn wearable device for the PWD, and a base station in the home. The BESI system collects large amounts of environmental data using dispersed relay stations that extract data from the home of the PWD. This data describes audio, light and other ambient stimuli inside the home. However, in order to understand how environmental factors impact agitation states, it must be understood what combination of factors cause agitation in PWD. BESI then uses this data combined with caregiver inputs to understand how to minimize or prevent agitation in the PWD, which is a major source of stress for caregivers. To analyze this data, it must be structured in a manner that is easier to work with. To structure the data, I prep large amounts of raw data, organize the data and reduce the data in an attempt to understand how environmental factors cause stress. The data structuring process is a key input to model the data using statistical models and machine learning to understand what environmental factors cause agitation in PWD. These methods can be utilized in medical and other studies and will advance our ability to design and develop effective cyber-human interventions for caregivers of PWD.

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