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1. Compressive sensing theoretical foundations in a nutshell
2. Recovery in compressive sensing: a review
3. A descriptive review to sparsity measures
4. Compressive sensing in practice and potential advancements
5. A review of deterministic sensing matrices
6. Deterministic compressive sensing by chirp codes: A descriptive tutorial
7. Deterministic compressive sensing by chirp codes: A MATLAB® tutorial
8. Cyber physical systems for healthcare applications using compressive sensing
9. Compressive sensing of electrocardiogram
10. Multichannel ECG reconstruction based on joint compressed sensing for healthcare applications
11. Neural signal compressive sensing
12. Level-crossing sampling: principles, circuits, and processing for healthcare applications
13. Compressive sensing of electroencephalogram: a review
14. Calibrationless parallel compressed sensing reconstruction for rapid magnetic resonance imaging
Compressive Sensing in Healthcare, part of the Advances in Ubiquitous Sensing Applications for Healthcare series gives a review on compressive sensing techniques in a practical way, also presenting 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 the use of EEG and ECG, plus hardware and software requirements for building projects. Body area networks and body sensor networks are explored.
- Provides a toolbox for compressive sensing in health, presenting both mathematical and coding information
- Presents an 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, and Medical Physics (focused on healthcare applications)
- No. of pages:
- © Academic Press 2021
- 20th May 2020
- Academic Press
- Paperback ISBN:
- eBook 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.
Visiting Associate Professor, Electrical Engineering Department, Federal Universit of Juiz de Fora, Sao Pedro, Brazil
Nilanjan Dey is an Assistant Professor in the Department of Information Technology at Techno India College of Technology, Kolkata, India. He is a visiting fellow of the University of Reading, UK, and is also a Visiting Professor at Wenzhou Medical University, China and Duy Tan University, Vietnam. He was an honorary Visiting Scientist at Global Biomedical Technologies Inc., CA, USA (2012-2015). He was awarded his PhD. from Jadavpur University in 2015. Dr. Dey has authored/edited more than 45 books with Elsevier, Wiley, CRC Press, and Springer, and published more than 300 papers. He is the Editor-in-Chief of International Journal of Ambient Computing and Intelligence, IGI Global, Associated Editor of IEEE Access and International Journal of Information Technology published by Springer. He is the Series Co-Editor of Springer Tracts in Nature-Inspired Computing, Springer Nature, Series Co-Editor of Advances in Ubiquitous Sensing Applications for Healthcare, Elsevier, Series Editor of Computational Intelligence in Engineering Problem Solving and Intelligent Signal processing and data analysis, CRC. His main research interests include medical imaging, machine learning, computer-aided diagnosis and data mining. He is the Indian Ambassador of International Federation for Information Processing (IFIP) – Young ICT Group and has recently been awarded as one among the top 10 most published academics in the field of Computer Science in India (2015-17).
Assistant Professor, Department of Information Technology, Techno India College of Technology, Kolkata, India
Carlos A. 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.
Full Professor, Electrical Engineering Faculty, Federal University of Juiz de Fora, Sao Pedro, Brazil
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