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Pervasive Quantied-Self using Multiple Sensors

Abstract The advent of commercial inexpensive sensors and the advances in information and communication technology (ICT) have brought forth the era of pervasive Quantified-Self. Automatic diet monitoring is one of the most important aspects for Quantified-Self because it is vital for ensuring the well-being of patients suffering from chronic diseases as well as for providing a low cost means for maintaining the health for everyone else. Automatic dietary monitoring consists of: a) Determining the type and amount of food intake, and b) Monitoring eating behavior, i.e., time, frequency, and speed of eating. Although there are some existing techniques towards these ends, they suffer from issues of low accuracy and low adherence. To overcome these issue... (more)
Created Date 2019
Contributor Lee, Junghyo (Author) / Gupta, Sandeep K.S. (Advisor) / Banerjee, Ayan (Committee member) / Li, Baoxin (Committee member) / Chiou, Erin (Committee member) / Kudva, Yogish C. (Committee member) / Arizona State University (Publisher)
Subject Computer engineering / Computer science / Electrical engineering / Diet monitoring / Gesture Recognition / Pervasive computing / Quantified-Self / Time-series Data Modeling / Wearable
Type Doctoral Dissertation
Extent 124 pages
Language English
Note Doctoral Dissertation Computer Engineering 2019
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis