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Section I. COMPRESSIVE SENSING THEORY
1. Compressive Sensing Theory and Implementation in a Nutshell
2. Deterministic Spectral Compressive Sensing by Chirp Codes
3. A MATLAB tutorial to Deterministic Compressive Sensing by Chirp Codes
Section II. APPLICATION TO HEALTH CARE
4. Compressive sensing in the field – Medical case studies
5. Cyber physical systems for healthcare applications using compressive sensing
6. Exploiting Prior Knowledge in Compressed Sensing Wireless ECG Systems
7. On Compressed Sensing and Classification of ECG and EEG Signals
8. Level-Crossing Sampling: Principles, Circuits, and Processing
9. Calibrationless Parallel Compressed Sensing Reconstruction for Rapid Magnetic Resonance Imaging
10. Multichannel ECG Reconstruction based on Joint Compressed Sensing for Healthcare Applications
11. Compressive Sensing of Electrocardiogram
Advances in Ubiquitous Sensing Applications for Healthcare is a series which covers new systems based on ubiquitous sensing for healthcare (USH). The volumes in this book series cover a wide range of interdisciplinary areas, and focus on U-healthcare systems in real-world healthcare applications. This book series demonstrates that this new domain is an outstanding and significant domain that has a brilliant future in applied healthcare research. The volumes in this series are ideal reference texts for engineers and researchers who are working on U-healthcare and mhealth systems. The volumes in this book series cover a wide range of interdisciplinary areas including wireless sensors networks, wireless body area networks, Big data, Internet-of-Things (IoT), security, monitoring, real time data collection, data management, systems design/analysis, web services and practical applications related to U-healthcare systems, implantable/wearable sensors in body sensor networks, information technology, diagnostic services, encryption, and implementation of wireless telemetry system for multisensory data fusion and decision-support.
Compressive Sensing in Healthcare gives a review of compressive sensing techniques in a practical way and presents deterministic compressive sensing techniques that can be used in the field. The focus of the book is on healthcare applications for this technology. It is intended for both the creators of this technology and the end users of these products. The content includes use of EEG and ECG, plus hardware and software requirements for building projects. Body area networks and body sensor networks are explored within this book. Throughout this next discusses new technological trends and design challenges for researchers.
- A toolbox for compressive sensing in health, providing mathematical and coding information
- Intuitive introduction to compressive sensing, including MATLAB tutorials
- Covers applications of compressive sensing in health care
Graduates, post-graduate students, post-docs and researchers and lecturers in Signal Processing, Biomedical Engineering, Computer Science , Medical Physics (focused on healthcare applications)
- No. of pages:
- © Academic Press 2020
- 1st May 2020
- Academic Press
- Paperback ISBN:
Mahdi Khosravy received BSc. in Electrical Engineering (bio-electric) from Sahand University of Technology, Tabriz, Iran, and MSc. in Biomedical Engineering (bio-electric) from Beheshti University of Medical Studies, Tehran, Iran. Mahdi received his Ph.D. in the field of Information Technology from University of Ryukyus, Okinawa, Japan. He was awarded by the head of University for his excellence in research. In September 2010, he joined University of Information Science and Technology (UIST), Ohrid, Macedonia, in the capacity of assistant professor. In 2016, he established a journal in information technology (ejist.uist.edu.mk) in UIST as currently hold its executive editorship. In July 2017, he became an associate professor. From August 2018 he joined the Energy lab in University of the Ryukyus as a Visiting Researcher. Since April 2018, he is a visiting associate professor in Electrical Engineering Department, Federal Universit of Juiz de For a in Brazil. Dr. Khosravy is a member of IEEE.
Received BSc. in Electrical Engineering (bio-electric) from Sahand University of Technology, Tabriz, Iran, and MSc. in Biomedical Engineering (bio-electric) from Beheshti University of Medical Studies, Tehran, Iran. Mahdi received his Ph.D. in the field of Information Technology from University of Ryukyus, Okinawa, Japan
Nilanjan Dey received his Ph. D. Degree from Jadavpur University, India, in 2015. He is an Assistant Professor in the Department of Information Technology, Techno International New Town, Kolkata, W.B., India. He holds an honorary position of Visiting Scientist at Global Biomedical Technologies Inc., CA, USA and Research Scientist of Laboratory of Applied Mathematical Modeling in Human Physiology, Territorial Organization of- Scientific and Engineering Unions, Bulgaria. Associate Researcher of Laboratoire RIADI, University of Manouba, Tunisia. His research topic is Medical Imaging, Data mining, Machine learning, Computer Aided Diagnosis, Atherosclerosis etc. He is the Editor-in-Chief of International Journal of Ambient Computing and Intelligence (IGI Global), US, International Journal of Rough Sets and Data Analysis (IGI Global), US, the International Journal of Synthetic Emotions (IGI Global), US, (Co-EinC) and International Journal of Natural Computing Research (IGI Global), US. Series Editor (Co.) of Advances in Ubiquitous Sensing Applications for Healthcare (AUSAH), Elsevier, Advances in Geospatial Technologies (AGT) Book Series, (IGI Global), US, Executive Editor of International Journal of Image Mining (IJIM), Inderscience, Associated Editor of IEEE Access and International Journal of Information Technology, Springer. He has 20 books and more than 200 research articles in peer-reviewed journals and international conferences. He is the organizing committee member of several international conferences including ITITS, W4C, ICMIR, FICTA, ICICT.
Assistant Professor, Department of Information Technology, Techno International New Town, Kolkata, India
Carlos Duque received the B.S. degree in Electrical Engineering from the Federal University of Juiz de Fora, Brazil, in 1986, and the M.Sc. and Ph.D. degree from the Catholic University of Rio de Janeiro, in 1990 and 1997, in Electrical Engineering. Since 1989 he is a Full Professor in the Electrical Engineering Faculty at Federal University of Juiz de Fora (UFJF), Brazil. During 2007-2008 he joined to the Centre for Advanced Power Systems (CAPS) at Florida State University as visiting researcher. His research areas are signal processing for power systems. He is currently the head of the Research Group of Signal Processing Applied to Power Systems- UFJF and associated researcher of the Brazil National Institute of Energy. Dr. Duque has written over 120 peer-reviewed papers and chapters of technical books. Professor Duque is the author of "Power System Signal Processing for Smart Grids " book, published in 2014 by Wiley.
Rreceived the B.S. degree in Electrical Engineering from the Federal University of Juiz de Fora, Brazil, in 1986, and the M.Sc. and Ph.D. degree from the Catholic University of Rio de Janeiro, in 1990 and 1997, in Electrical Engineering.