Full metadata
Title
Pervasive quantied-self using multiple sensors
Pervasive quantified-self using multiple sensors
Description
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 issues, multiple sensors were utilized because the availability of affordable sensors that can capture the different aspect information has the potential for increasing the available knowledge for Quantified-Self. For a), I envision an intelligent dietary monitoring system that automatically identifies food items by using the knowledge obtained from visible spectrum camera and infrared spectrum camera. This system is able to outperform the state-of-the-art systems for cooked food recognition by 25% while also minimizing user intervention. For b), I propose a novel methodology, IDEA that performs accurate eating action identification within eating episodes with an average F1-score of 0.92. This is an improvement of 0.11 for precision and 0.15 for recall for the worst-case users as compared to the state-of-the-art. IDEA uses only a single wrist-band which includes four sensors and provides feedback on eating speed every 2 minutes without obtaining any manual input from the user.
Date Created
2019
Contributors
- Lee, Junghyo (Author)
- Gupta, Sandeep K.S. (Thesis advisor)
- Banerjee, Ayan (Committee member)
- Li, Baoxin (Committee member)
- Chiou, Erin (Committee member)
- Kudva, Yogish C. (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
xi,112 pages : color illustrations
Language
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.I.54901
Statement of Responsibility
by Junghyo Lee
Description Source
Viewed on August 25, 2020
Level of coding
full
Note
Partial requirement for: Ph.D., Arizona State University, 2019
Note type
thesis
Includes bibliographical references
Note type
bibliography
Field of study: Computer engineering
System Created
- 2019-11-06 03:39:17
System Modified
- 2021-08-26 09:47:01
- 2 years 8 months ago
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