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Generalizable Methodology for Measur...

Makhsous, Sepehr.

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Generalizable Methodology for Measurement and Analysis of Nutritional Intake.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Generalizable Methodology for Measurement and Analysis of Nutritional Intake./
作者:	Makhsous, Sepehr.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
面頁冊數:	160 p.
附註:	Source: Dissertations Abstracts International, Volume: 82-05, Section: B.
Contained By:	Dissertations Abstracts International82-05B.
標題:	Electrical engineering. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28025473
ISBN:	9798684650369

Generalizable Methodology for Measurement and Analysis of Nutritional Intake.
Makhsous, Sepehr.

Generalizable Methodology for Measurement and Analysis of Nutritional Intake. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 160 p.

Source: Dissertations Abstracts International, Volume: 82-05, Section: B.

Thesis (Ph.D.)--University of Washington, 2020.

This item must not be sold to any third party vendors.

According to the American Cancer Society (ACS), in 2018, more than 17 million people were diagnosed with cancer, and over 9 million patients died of cancer. Recent studies show that diet and lifestyle were two of the most common risk factors for related diseases and cancer. In Epidemiologic studies, enhanced dietary measurement tools are used to collect and analyze nutritional data. Traditional nutritional measurement methods include manual measurements and self-reporting, which introduce problems such as: 1) misreporting, 2) human error, and 3) involuntarily change of dietary habit. Recent advancements in sensing technologies have allowed for the development of various 3D measurement techniques for different applications. However, epidemiologists are still using self-reporting systems rather than automated 3D measurement tools, which demonstrates that there is significant room for improvement in this field. The volumetric measurement of a 3D object requires an accurate depth calculation using reference-based or depth sensing estimation techniques. This dissertation is a study of the design, modeling, and integration of a 3D measurement system based on the structured light system (SLS) theory. The system was designed, developed, and evaluated in dietary assessment applications, such as cancer and diabetes, using both a customized 3D scanner and a commercial off the shelf (COTS) depth sensor. The participants were selected randomly to test the system in different use-cases. When compared to similar systems, the results showed an average increase in accuracy of 30% and a reduction in measurement time by more than a factor of three. Based on the results and feedback from the researchers and users, the use of low-cost depth sensors in 3D measurement have drastically improved the quality of automated nutritional analysis. In addition to dietary assessment applications, the system was further developed and tested in other epidemiological fields, such as wound care management, air quality monitoring, and environmental disease tracking.

ISBN: 9798684650369Subjects--Topical Terms:

649834
Electrical engineering.
Subjects--Index Terms:

3D Reconstruction

Generalizable Methodology for Measurement and Analysis of Nutritional Intake.
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520 $a According to the American Cancer Society (ACS), in 2018, more than 17 million people were diagnosed with cancer, and over 9 million patients died of cancer. Recent studies show that diet and lifestyle were two of the most common risk factors for related diseases and cancer. In Epidemiologic studies, enhanced dietary measurement tools are used to collect and analyze nutritional data. Traditional nutritional measurement methods include manual measurements and self-reporting, which introduce problems such as: 1) misreporting, 2) human error, and 3) involuntarily change of dietary habit. Recent advancements in sensing technologies have allowed for the development of various 3D measurement techniques for different applications. However, epidemiologists are still using self-reporting systems rather than automated 3D measurement tools, which demonstrates that there is significant room for improvement in this field. The volumetric measurement of a 3D object requires an accurate depth calculation using reference-based or depth sensing estimation techniques. This dissertation is a study of the design, modeling, and integration of a 3D measurement system based on the structured light system (SLS) theory. The system was designed, developed, and evaluated in dietary assessment applications, such as cancer and diabetes, using both a customized 3D scanner and a commercial off the shelf (COTS) depth sensor. The participants were selected randomly to test the system in different use-cases. When compared to similar systems, the results showed an average increase in accuracy of 30% and a reduction in measurement time by more than a factor of three. Based on the results and feedback from the researchers and users, the use of low-cost depth sensors in 3D measurement have drastically improved the quality of automated nutritional analysis. In addition to dietary assessment applications, the system was further developed and tested in other epidemiological fields, such as wound care management, air quality monitoring, and environmental disease tracking.
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