자료유형  

 학위논문

Control Number  

0016933200

International Standard Book Number  

9798379907822

Dewey Decimal Classification Number  

004

Main Entry-Personal Name  

Liu, Xin.

Publication, Distribution, etc. (Imprint  

[S.l.] : University of Washington., 2023

Publication, Distribution, etc. (Imprint  

Ann Arbor : ProQuest Dissertations & Theses, 2023

Physical Description  

1 online resource(176 p.)

General Note  

Source: Dissertations Abstracts International, Volume: 85-01, Section: B.

General Note  

Advisor: Patel, Shwetak N.

Dissertation Note  

Thesis (Ph.D.)--University of Washington, 2023.

Restrictions on Access Note  

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

Summary, Etc.  

요약The COVID-19 pandemic has prompted a shift in the delivery of healthcare globally, with a growing emphasis on scalable health sensing. Currently, biomedical contact sensors are considered the gold standard for measuring vital signals, but they are not widely accessible, particularly in under-resourced areas. Camera-based health sensing offers the potential to reach a wider population by using regular RGB cameras to detect changes in electromagnetic radiation (light) reflected from the body that result from physiological processes. However, existing camera-based health sensing methods are inaccessible due to their high computational costs, inequitable due to poor generalizability across skin tones, lighting, and movements, and not fully validated for use in clinical settings. To address these challenges, this thesis explores the development of on-device neural networks, few-shot adaptation, federated learning, and data augmentation systems and algorithms for camera-based health sensing. A transnational clinical study is also conducted to evaluate the usefulness of these methods in real-world clinical settings and to advance the field of camera-based health sensing beyond well-studied physiological signals. Finally, this research introduces an open-source toolbox to promote reproducibility and fair benchmarking comparisons.

Subject Added Entry-Topical Term  

Computer science.

Subject Added Entry-Topical Term  

Engineering.

Index Term-Uncontrolled  

Computer vision

Index Term-Uncontrolled  

Health sensing

Index Term-Uncontrolled  

Machine learning

Index Term-Uncontrolled  

Ubiquitous computing

Added Entry-Corporate Name  

University of Washington Computer Science and Engineering

Host Item Entry  

Dissertations Abstracts International. 85-01B.

Host Item Entry  

Dissertation Abstract International

Electronic Location and Access  

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Control Number  

joongbu:642294