The Physical Characterization of Human Autonomic Responses and Health in a Variety of Environmental and Social Contexts

Date

December 2023

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Abstract

The human body responds to environmental stimuli in a variety of ways. Combining the physical measurements autonomic responses such as eye movement, heart rate and sweat response may provide a robust characterization of millisecond human interactions with the surrounding environment. Furthermore, the environment directs health outcomes through long-term exposures, which is explored in conjunction with hospitalization data. This thesis also explores a method to detect blinks that would aid in quantifying concepts such as cognitive load, and finally, a software suite for comprehensively analyzing brain, eye, and audio data to dynamically explore the coupled nature of metrics and an application of these techniques to a variety of everyday and specialized activities. Various machine learning techniques are used to analyze this high-dimensional feature-rich data space and to automate the extraction of interesting events.

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Physics, Atmospheric Science

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