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Pervasive Cardiovascular and Respiratory Monitoring Devices
Model-Based Design
1st Edition - June 22, 2023
Author: Miodrag Bolic
Paperback ISBN:9780128209479
9 7 8 - 0 - 1 2 - 8 2 0 9 4 7 - 9
eBook ISBN:9780128209486
9 7 8 - 0 - 1 2 - 8 2 0 9 4 8 - 6
Pervasive Cardiac and Respiratory Monitoring Devices: Model-Based Design is the first book to combine biomedical instrumentation and model-based design. As the scope is limited to… Read more
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Pervasive Cardiac and Respiratory Monitoring Devices: Model-Based Design is the first book to combine biomedical instrumentation and model-based design. As the scope is limited to cardiac and respiratory devices only, this book offers more depth of information on these devices; focusing in on signals used for home monitoring and offering additional analysis of these devices. The author offers an insight into new industry and research trends, including advances in contactless monitoring of breathing and heart rate. Each chapter presents a section on current trends. As instrumentation as a field is becoming increasingly smart, basic signal processing is also discussed. Real case-studies for each modelling approach are used, primarily covering blood pressure, ECG and radar-based devices.
This title is ideal for teaching and supporting learning as it is written in an accessible style and a solutions manual for the problem sets is provided. It will be useful to 4th year undergraduate students, graduate/masters/PhD students, early career researchers and professionals working on an interdisciplinary project; as it introduces the field and provides real world applications. For engineers this book solves the problem of how to assess and calibrate a medical device to ensure the data collected is trustworthy. For students, this book allows for trying concepts and circuits via simulations and learning modeling techniques. Students will learn concepts from this book and be ready to design bioinstrumentations devices based on specifications/requirements.
Focuses on model-based design using Simscape/MATLAB; learn how to design a system and how to evaluate how different choices affect the output of the system
Covers pervasive monitoring: shows how to design optimal solutions for pervasive and personalized healthcare monitoring
Explores uncertainty and sensitivity analysis; understand your model better
Cover image
Title page
Table of Contents
Copyright
Dedication
Preface
Acknowledgments
Overview of biomedical instrumentation and devices
Abstract
Abbreviations and explanations
1. Introduction
2. Pervasive devices
3. Biomedical devices for cardiac and respiratory monitoring
4. Modeling and simulation
5. Design cycle
6. Biomedical device components and design issues
7. Organization of the book
8. Summary
9. Problems
10. Further reading
Chapter 1. Concepts in performance evaluation and uncertainty analysis
1.1. Introduction
1.2. Basic probabilistic concepts
1.3. Performance metrics
1.4. Measuring agreement
1.5. Uncertainty in measurements
1.6. Summary
1.7. Problems
1.8. Further reading
Chapter 2. Transducers
2.1. Introduction
2.2. Strain gauges
2.3. Piezoelectric transducers
2.4. Capacitive transducers
2.5. Optical sensors
2.6. Electrodes
2.7. Summary
2.8. Appendix
2.9. Problems
2.10. Further reading
Chapter 3. Electronics
3.1. Introduction
3.2. Wheatstone bridge
3.3. Amplifiers and their configurations
3.4. Analog filters
3.5. Analog-to-digital converter
3.6. Generating signals
3.7. Other components of the system
3.8. Summary
3.9. Problems
3.10. Further reading
Chapter 4. Modeling and simulation of biomedical systems
4.1. Introduction
4.2. Data collection and databases
4.3. Models for signal generation
4.4. Modeling noise and assessing signal quality
4.5. Uncertainty propagation in systems
4.6. Modeling software
4.7. Modeling power consumption
4.8. Summary
4.9. Problems
4.10. Further reading
Chapter 5. Devices based on oscillometric signal: blood pressure
5.1. Introduction
5.2. What is measured using a blood pressure device
5.3. Features of the signal and the noise
5.4. Performance measures and evaluation
5.5. Oscillometric signal generation model
5.6. Oscillometric algorithm
5.7. Sensors and circuits
5.8. Simulation of the overall system
5.9. Improving oscillometric methods and devices
5.10. Oscillometry and arterial stiffness
5.11. Summary
5.12. Appendix A
5.13. Problems
5.14. Further reading
Chapter 6. Devices based on photoplethysmogram and pulse oximetry
6.1. Introduction
6.2. What is measured using pulse oximeters and PPG devices?
6.3. Signal properties and noise characterization
6.4. Performance measures
6.5. Simulating the propagation of light through the tissue in reflectance-mode pulse oximetry
6.6. Sensors and circuits
6.7. PPG system
6.8. Pulse oximeters
6.9. New developments
6.10. Summary
6.11. Problems
6.12. Further reading
Chapter 7. Devices based on the ECG signal
7.1. Introduction
7.2. What is measured using ECG
7.3. Signal properties, simulators, and databases
7.4. Types of devices and standards
7.5. Processing the ECG signal
7.6. Implementation of a single-lead ECG system
7.7. Current trends and research directions
7.8. Heart rate variability
7.9. Summary
7.10. Appendix: segmentation of the ECG signal
7.11. Problems
7.12. Further reading
Chapter 8. Devices based on the time difference between signals: continuous blood pressure measurement
8.1. Introduction
8.2. Temporal relationship between signals
8.3. Modeling the relationship between PTT and blood pressure
11.6. Combining all: pervasive health monitoring systems
11.7. Conclusion
Index
No. of pages: 488
Language: English
Published: June 22, 2023
Imprint: Academic Press
Paperback ISBN: 9780128209479
eBook ISBN: 9780128209486
MB
Miodrag Bolic
Miodrag Bolic received his Ph.D. degree in electrical engineering from Stony Brook University, US, in 2004. Since 2004 he has been with the University of Ottawa, Canada where he is Professor with the School of Electrical Engineering and Computer Science. He is a Director of the Computational Analysis and Health Devices research groups. His current research interests include physics based machine learning and uncertainty quantification for biomedical and autonomous vehicles applications. He has published about 80 journal papers and has 5 patents. He teaches at the graduate level courses on biomedical instrumentation and uncertainty quantification in engineering and machine learning.
Prof. Bolic worked on cardiorespiratory monitoring for the last 12 years including both the design of devices and development of signal processing/machine learning algorithms. His work on wearable devices include ECG-assisted oscillometric and BCG-assisted cuffless blood pressure monitoring. His work on contactless monitoring includes breathing and heart rate estimation and breathing pattern classification using RGB, thermal and 3D cameras as well as radars.