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|a Contactless vital signs monitoring /
|c edited by Wenjin Wang and Xuyu Wang.
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|a London :
|b Academic Press,
|c 2022.
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|a Front Cover -- Contactless Vital Signs Monitoring -- Copyright -- Contents -- List of contributors -- Foreword -- Preface -- 1 Human physiology and contactless vital signs monitoring using camera and wireless signals -- 1.1 Contactless vital signs monitoring with cameras and wireless -- 1.2 Camera-based vital signs monitoring -- 1.3 Current techniques of camera-based vital signs monitoring -- 1.3.1 Camera-based pulse monitoring -- 1.3.2 Cardiac-related physiological signals using camera-based methods -- 1.3.2.1 Heart rate -- 1.3.2.2 Blood oxygen saturation -- 1.3.2.3 Blood pressure -- 1.3.3 Camera-based respiration monitoring -- 1.3.4 Camera-based body temperature monitoring -- 1.4 Applications of camera-based vital signs monitoring -- 1.4.1 Clinical applications -- 1.4.2 Free-living applications -- 1.5 Wireless-based vital signs monitoring -- 1.6 Current techniques of wireless-based vital signs monitoring -- 1.6.1 Radar-based vital signs monitoring -- 1.6.2 RSS-based vital signs monitoring -- 1.6.3 CSI-based vital signs monitoring -- 1.6.4 RFID-based vital signs monitoring -- 1.6.5 Acoustic-based vital signs monitoring -- 1.7 Conclusions -- Acknowledgments -- References -- Part I Camera-based vital signs monitoring -- 2 Physiological origin of camera-based PPG imaging -- 2.1 Introduction -- 2.2 Conventional PPG model: blood volume modulation -- 2.3 How to explain the largest modulation of the green light? -- 2.4 Alternative PPG model: tissue compression modulation -- 2.5 Boundary conditions and influence of skin contact -- 2.6 Pulsatile dermis compression and modulation of IR light -- 2.7 Light modulation in a single capillary -- 2.8 Irregularity of RBC motion -- 2.9 Occlusion plethysmography -- 2.10 Peculiarities of light interaction with cerebral vessels -- 2.11 APC as a measure of the arterial tone.
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|a 2.12 Green-light camera-based PPG and cutaneous perfusion -- 2.13 Conclusive remarks -- Acknowledgments -- References -- 3 Model-based camera-PPG -- 3.1 Introduction -- 3.2 Model-based pulse rate extraction -- 3.3 Fitness application -- 3.3.1 Experimental setup -- 3.3.2 Processing chain -- 3.3.3 Performance metric -- 3.4 Results -- 3.4.1 Reference creation -- 3.4.2 System performance -- 3.5 Discussion -- 3.6 Conclusions -- 3.A PBV determination -- 3.A.1 Optical path descriptors -- 3.A.2 Experimental PBV determination -- 3.B Pseudocode for model-based PPG -- References -- 4 Camera-based respiration monitoring -- 4.1 Introduction -- 4.2 Setup and measurements -- 4.2.1 Camera setup in the MR system -- 4.2.2 Data collection and preparation -- 4.3 Methods -- 4.3.1 PPG-based -- 4.3.2 Motion-based: optical flow -- 4.3.3 Motion-based: profile correlation -- 4.3.4 Respiratory signal and rate -- 4.4 Results and discussion -- 4.5 Conclusions -- References -- 5 Camera-based blood oxygen measurement -- 5.1 Introduction -- 5.2 Principle -- 5.3 Application: monitoring blood oxygen saturation in human skin -- 5.4 Application: monitoring blood oxygen saturation in skin during changes in fraction of inspired oxygen -- 5.5 Application: monitoring blood oxygen saturation in brain -- 5.6 Application: monitoring blood oxygen saturation in hepatic ischemia-reperfusion -- References -- 6 Camera-based blood pressure monitoring -- 6.1 Advantages over other potential cuff-less BP measurement devices -- 6.2 Theoretical principles -- 6.2.1 Contactless acquisition of arterial waveforms -- 6.2.2 Extraction of waveform features that correlate with BP -- 6.2.3 Calibration of features to BP using cuff BP measurements -- 6.3 Summary of previous experimental studies -- 6.3.1 Key camera-based BP monitoring investigations -- 6.3.2 Relevant contact-sensor BP monitoring investigations.
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|a 6.4 Conclusions -- 6.4.1 Summary -- 6.4.2 Future research directions -- 6.4.3 Outlook -- Acknowledgments -- References -- 7 Clinical applications for imaging photoplethysmography -- 7.1 Overview -- 7.2 Patient monitoring and risk assessment -- 7.2.1 Current monitoring-target groups and technology -- 7.2.2 Patient monitoring by iPPG-measures of relevance -- 7.2.3 Patient monitoring by iPPG-realistic usage scenarios -- 7.3 Application beyond patient monitoring -- 7.3.1 Sleep medicine -- 7.3.2 Local perfusion analysis -- 7.3.3 Skin microcirculation as diagnostic proxy -- 7.3.4 Further applications -- 7.4 Summary and outlook -- Acknowledgments -- References -- 8 Applications of camera-based physiological measurement beyond healthcare -- 8.1 The evolution from the lab to the real world -- 8.2 The promise for ubiquitous computing -- 8.2.1 Fitness and wellness -- 8.2.2 Affective computing -- 8.2.3 Biometric recognition and liveness detection -- 8.2.4 Avatars, remote communication, and mixed reality -- 8.3 Challenges -- 8.4 Ethics and privacy implications -- 8.5 Regulation -- 8.6 Summary -- References -- Part II Wireless sensor-based vital signs monitoring -- 9 Radar-based vital signs monitoring -- 9.1 Introduction -- 9.2 Vital signs monitoring through continuous-wave radar -- 9.2.1 Theory -- 9.2.1.1 Basic theory -- 9.2.1.2 Phase demodulation algorithm -- 9.2.1.3 Advancements in CW radar -- 9.2.2 Vital signs monitoring -- 9.2.2.1 Cardiopulmonary monitoring -- 9.2.2.2 Cancer medical application -- 9.3 Vital signs monitoring using FMCW radar -- 9.3.1 Composition of an FMCW radar system -- 9.3.2 Analysis of an FMCW radar IF signal -- 9.3.3 FMCW radar parameter estimation -- 9.3.3.1 FMCW radar range estimation -- 9.3.3.2 FMCW radar velocity estimation -- 9.3.3.3 FMCW radar angle estimation.
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|a 9.3.3.4 FMCW radar phase-based range-tracking algorithm for vital signs monitoring -- 9.3.4 Examples of FMCW radar on contactless vital signs monitoring -- 9.3.4.1 Respiration monitoring -- 9.3.4.2 Indoor human tracking -- 9.3.4.3 Hybrid radar systems for human tracking and identification -- 9.3.4.4 Other types of FMCW radar vital signs detection applications -- 9.4 Conclusion -- References -- 10 Received power-based vital signs monitoring -- 10.1 Introduction -- 10.2 Related work -- 10.2.1 Radar approaches -- 10.2.2 Repurposing wireless transceivers -- 10.3 Received power-based vital signs monitoring -- 10.3.1 Received power model -- 10.3.2 Estimating rates from received power -- 10.4 Implementation -- 10.4.1 Hardware -- 10.4.2 Software -- 10.4.3 Experimental setup -- 10.5 Experimental results -- 10.5.1 Breathing-rate accuracy -- 10.5.1.1 Respiration-rate estimation with controlled breathing -- 10.5.1.2 Respiration-rate estimation with short-term uncontrolled breathing -- 10.5.1.3 Respiration-rate estimation with long-term uncontrolled breathing -- 10.5.2 Pulse-rate accuracy -- 10.6 Conclusion -- References -- 11 WiFi CSI-based vital signs monitoring -- 11.1 Introduction -- 11.2 An historic review of WiFi-based human respiration monitoring -- 11.2.1 RSS-based respiration monitoring -- 11.2.2 CSI-based respiration monitoring -- 11.3 The principle of WiFi CSI-based respiration monitoring -- 11.3.1 The basics of WiFi CSI -- 11.3.2 Modeling human respiration -- 11.3.3 Fresnel diffraction and reflection sensing models -- 11.4 Robust single-person respiration monitoring -- 11.4.1 Removing ``blind spots'' for respiration monitoring -- 11.4.1.1 Exploiting complementarity of CSI amplitude and phase -- 11.4.1.2 Adding `a `virtual'' multipath -- 11.4.2 Pushing the sensing range of respiration monitoring -- 11.4.2.1 The CSI-ratio model.
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|a 11.4.2.2 Applying CSI ratio to single-person respiration sensing -- 11.4.2.3 Evaluation -- 11.5 Robust multi-person respiration monitoring -- 11.5.1 Modeling of CSI-based multi-person respiration sensing -- 11.5.1.1 Effects of multi-person respiration on WiFi CSI -- 11.5.1.2 Modeling multi-person respiration sensing as a blind-source separation problem -- 11.5.2 The advantages of our approach -- 11.5.2.1 Reducing the noise in CSI amplitude -- 11.5.2.2 Eliminating the ``blind spots'' -- 11.5.2.3 Resolving similar respiration rates -- 11.5.3 Evaluation -- 11.5.3.1 Experimental setup -- 11.5.3.2 Experiment results -- 11.6 Summary -- Acknowledgments -- References -- 12 RFID-based vital signs monitoring -- 12.1 Introduction -- 12.2 Background -- 12.2.1 Literature review -- 12.2.1.1 RFID sensing -- 12.2.1.2 Wireless-based vital signs monitoring -- 12.2.1.3 RFID-based vital signs monitoring -- 12.2.1.4 Respiration monitoring system -- 12.2.2 RFID physical-layer measurement -- 12.3 Respiration monitoring using RFID systems -- 12.3.1 System overview -- 12.3.2 Low-level data characterization -- 12.3.3 Breath signal extraction -- 12.3.4 Enhance monitoring with sensor fusion of multiple tags -- 12.3.5 Discussion -- 12.4 Implementation and evaluation -- 12.4.1 Implementation -- 12.4.2 Experiment setting -- 12.4.3 Experiment results -- 12.5 Conclusion -- References -- 13 Acoustic-based vital signs monitoring -- 13.1 Introduction -- 13.2 Related work -- 13.3 Sonar phase analysis -- 13.4 The SonarBeat system -- 13.4.1 SonarBeat system architecture -- 13.4.2 Signal generation -- 13.4.3 Data extraction -- 13.4.4 Received signal preprocessing -- 13.4.4.1 I/Q demodulation -- 13.4.4.2 Static vector effect reduction -- 13.5 Experimental study -- 13.5.1 Implementation and test configuration -- 13.5.2 Performance of breathing-rate estimation.
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|a Vital signs
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|a Wang, Wenjin.
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|a Wang, Xuyu.
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|i Print version:
|z 0128222816
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|w (OCoLC)1245656093
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| 776 |
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|i Print version:
|t CONTACTLESS VITAL SIGNS MONITORING.
|d [S.l.] : ELSEVIER ACADEMIC PRESS, 2021
|z 0128222816
|w (OCoLC)1245656093
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| 856 |
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0 |
|u https://sciencedirect.uam.elogim.com/science/book/9780128222812
|z Texto completo
|
