Electronic Theses and Dissertations
Identifier
6105
Date
2017
Document Type
Thesis
Degree Name
Master of Science
Major
Electrical and Computer Engr
Concentration
Computer Engineering
Committee Chair
Bonny Banerjee
Committee Member
Madhusudhanan Balasubramanian
Committee Member
Aaron L. Robinson
Abstract
Data is the key for developing algorithms that can infer the causes of agitation in mentally-ill individuals. Unfortunately, appropriate datasets are not readily available due to issues such as confidentiality breach and privacy invasion. This thesis addresses three problems.First, we identify a number of publicly-available datasets that are functions of actions and emotions of mentally-ill individuals. These include datasets of physiological signals, training videos and commercial movies.Second, we synthesize change in body-weight as a function of actions and emotions by extending a well-known model. The extended model is evaluated with respect to change in diet, physical activity and stress, using data reported in the literature. The evaluation results show promise.Third, we propose an efficient way to store several physiological signals with different sampling frequencies. Instead of storing every sample of each signal, a linear interpolation-based approach synchronizes the signals at the desired sampling rate as and when needed.
Library Comment
Dissertation or thesis originally submitted to the local University of Memphis Electronic Theses & dissertation (ETD) Repository.
Recommended Citation
Koirala, Dewashish, "Data collection, body-weight generation and efficient storage of physiological data" (2017). Electronic Theses and Dissertations. 1781.
https://digitalcommons.memphis.edu/etd/1781
Comments
Data is provided by the student.