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    Biosymbiotic Wearable Platform for High-Fidelity Monitoring of Biosignals for Personalized Wound Care

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    Name:
    azu_etd_21924_sip1_m.pdf
    Embargo:
    2027-01-13
    Size:
    7.691Mb
    Format:
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    Author
    Gummalla, Venkata Sai Srilekha
    Issue Date
    2024
    Keywords
    biosymbiotic
    chronic
    wearable
    wound
    Advisor
    Gutruf, Philipp
    
    Metadata
    Show full item record
    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Embargo
    Release after 01/13/2027
    Abstract
    Chronic wounds require continuous assessment to ensure timely and effective treatment, yet traditional monitoring methods are limited by intermittent evaluations and the inability to capture real-time wound dynamics. Current solutions for wound monitoring, such as temperature-sensing insoles or pH-sensitive hydrogels, fall short due to their single-parameter focus, limited durability, or need for frequent replacements. In this work, we introduce a fully integrated biosymbiotic wearable device capable of long-term, multi-parameter wound assessment through sensors measuring tissue oxygenation, humidity, and thermal conductivity. The flexible structure of the biosymbiotic device enables comfortable, continuous wear while power management solutions support long-term operation suitable for continuous physiological monitoring and wireless recharging. Validation across benchtop, on-body, and preliminary clinical tests confirms stable and reliable sensor performance over time, demonstrating the ability of the biosymbiotic device to detect early signs of healing complications without direct patient intervention. This biosymbiotic device sets a foundation for real-time, responsive wound care, advancing toward a future of seamless, data-driven healthcare at home and in clinical settings.
    Type
    text
    Electronic Thesis
    Degree Name
    M.S.
    Degree Level
    masters
    Degree Program
    Graduate College
    Biomedical Engineering
    Degree Grantor
    University of Arizona
    Collections
    Master's Theses

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