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Intelligent Wearable Optical Sensing: Multimodal, Multichannel, and Multi-Wavelength Approaches for Advanced Physiological Monitoring
Intelligent Wearable Optical Sensing: Multimodal, Multichannel, and Multi-Wavelength Approaches for Advanced Physiological Monitoring
Detailed Information
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260202105308
- ISBN
- 9798270289478
- DDC
- 620.11
- 저자명
- Liu, Yihan.
- 서명/저자
- Intelligent Wearable Optical Sensing: Multimodal, Multichannel, and Multi-Wavelength Approaches for Advanced Physiological Monitoring
- 발행사항
- [Sl] : The University of North Carolina at Chapel Hill, 2025
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2025
- 형태사항
- 200 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 87-07, Section: B.
- 주기사항
- Advisor: Bai, Wubin.
- 학위논문주기
- Thesis (Ph.D.)--The University of North Carolina at Chapel Hill, 2025.
- 초록/해제
- 요약Wearable optical sensing holds significant promise for personalized medicine, yet its translation to robust, real-world applications is hindered by fundamental limitations. This dissertation, "Intelligent Wearable Optical Sensing: Multimodal, Multichannel, and Multi-Wavelength Approaches for Advanced Physiological Monitoring," confronts critical barriers in non-invasive sensing, including superficial light penetration, signal corruption from motion, low spatial resolution, and biochemical non-specificity. This work presents a series of advanced, skin-interfaced optical systems that integrate novel hardware design with intelligent computational methods to achieve new sensing capabilities.To access deeper physiological information, a novel interface utilizing biocompatible microneedle waveguides is introduced, creating a photonic pathway that bypasses superficial tissue to enable reliable deep-tissue oximetry monitoring. To address the challenges of ambulatory use and complex signal interpretation, multimodal and multichannel systems are developed. One such system fuses optical data with inertial measurements, employing a computational architecture to effectively isolate true laryngeal muscle activity from motion artifacts. Another platform, a high-resolution optical myography array, generates detailed spatiotemporal maps of muscle dynamics. This system leverages advanced data-processing techniques to interpret complex gestures, enabling robust human-machine interaction. Finally, to move beyond conventional oximetry, a multi-wavelength spectroscopic sensor performs real-time, non-invasive quantification of a specific blood analyte. By optically deconvolving the unique spectral signature of ethanol from capillary blood, this wrist-worn device demonstrates a viable pathway toward direct, continuous monitoring of blood biochemistry.Overall, the investigations in this dissertation demonstrate effective solutions to long-standing barriers in wearable optical sensing. By thoughtfully combining advancements in optical interfacing, sensor dimensionality, and signal processing, this work delivers a validated toolkit of new sensing strategies. These contributions lay the groundwork for a new generation of reliable, non-invasive devices for personalized diagnostics, advanced assistive technologies, and more intuitive human-machine interfacing.
- 일반주제명
- Materials science
- 일반주제명
- Physiology
- 일반주제명
- Biomedical engineering
- 키워드
- Machine learning
- 기타저자
- The University of North Carolina at Chapel Hill Materials Science
- 기본자료저록
- Dissertations Abstracts International. 87-07B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■020 ▼a9798270289478
■035 ▼a(MiAaPQ)AAI32283661
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a620.11
■1001 ▼aLiu, Yihan.
■24510▼aIntelligent Wearable Optical Sensing: Multimodal, Multichannel, and Multi-Wavelength Approaches for Advanced Physiological Monitoring
■260 ▼a[Sl]▼bThe University of North Carolina at Chapel Hill▼c2025
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2025
■300 ▼a200 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 87-07, Section: B.
■500 ▼aAdvisor: Bai, Wubin.
■5021 ▼aThesis (Ph.D.)--The University of North Carolina at Chapel Hill, 2025.
■520 ▼aWearable optical sensing holds significant promise for personalized medicine, yet its translation to robust, real-world applications is hindered by fundamental limitations. This dissertation, "Intelligent Wearable Optical Sensing: Multimodal, Multichannel, and Multi-Wavelength Approaches for Advanced Physiological Monitoring," confronts critical barriers in non-invasive sensing, including superficial light penetration, signal corruption from motion, low spatial resolution, and biochemical non-specificity. This work presents a series of advanced, skin-interfaced optical systems that integrate novel hardware design with intelligent computational methods to achieve new sensing capabilities.To access deeper physiological information, a novel interface utilizing biocompatible microneedle waveguides is introduced, creating a photonic pathway that bypasses superficial tissue to enable reliable deep-tissue oximetry monitoring. To address the challenges of ambulatory use and complex signal interpretation, multimodal and multichannel systems are developed. One such system fuses optical data with inertial measurements, employing a computational architecture to effectively isolate true laryngeal muscle activity from motion artifacts. Another platform, a high-resolution optical myography array, generates detailed spatiotemporal maps of muscle dynamics. This system leverages advanced data-processing techniques to interpret complex gestures, enabling robust human-machine interaction. Finally, to move beyond conventional oximetry, a multi-wavelength spectroscopic sensor performs real-time, non-invasive quantification of a specific blood analyte. By optically deconvolving the unique spectral signature of ethanol from capillary blood, this wrist-worn device demonstrates a viable pathway toward direct, continuous monitoring of blood biochemistry.Overall, the investigations in this dissertation demonstrate effective solutions to long-standing barriers in wearable optical sensing. By thoughtfully combining advancements in optical interfacing, sensor dimensionality, and signal processing, this work delivers a validated toolkit of new sensing strategies. These contributions lay the groundwork for a new generation of reliable, non-invasive devices for personalized diagnostics, advanced assistive technologies, and more intuitive human-machine interfacing.
■590 ▼aSchool code: 0153.
■650 4▼aMaterials science
■650 4▼aPhysiology
■650 4▼aBiomedical engineering
■653 ▼aHuman-machine interfacing
■653 ▼aMachine learning
■653 ▼aMultimodal biosensors
■653 ▼aNear-infrared spectroscopy
■653 ▼aPhysiological monitoring
■653 ▼aWearable optical sensing
■690 ▼a0794
■690 ▼a0541
■690 ▼a0800
■690 ▼a0719
■71020▼aThe University of North Carolina at Chapel Hill▼bMaterials Science.
■7730 ▼tDissertations Abstracts International▼g87-07B.
■790 ▼a0153
■791 ▼aPh.D.
■792 ▼a2025
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17360124▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
