Compressive Sensing in Healthcare

Erscheinungsjahr 2020
ISBN: 978-0-12-821247-9
Verlag: ACADEMIC PR INC

Buch, Englisch, Band 11, 306 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 612 g

Reihe: Advances in Ubiquitous Sensing

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.

Zielgruppe

Graduates, post-graduate students, post-docs and researchers and lecturers in Signal Processing, Biomedical Engineering, Computer Science , Medical Physics (focused on healthcare applications).

Autoren/Hrsg.

Khosravy, Mahdi

Dey, Nilanjan

Duque, Carlos A.

Fachgebiete

• Naturwissenschaften Physik Angewandte Physik Medizinische Physik
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Signalverarbeitung
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe

Inhaltsverzeichnis

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

Über Autor(innen)

Khosravy, Mahdi
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.

Dey, Nilanjan
Nilanjan Dey (Senior Member, IEEE) received the B.Tech., M.Tech. in information technology from West Bengal Board of Technical University and Ph.D. degrees in electronics and telecommunication engineering from Jadavpur University, Kolkata, India, in 2005, 2011, and 2015, respectively. Currently, he is Associate Professor with the Techno International New Town, Kolkata and a visiting fellow of the University of Reading, UK. He has authored over 300 research articles in peer-reviewed journals and international conferences and 40 authored books. His research interests include medical imaging and machine learning. Moreover, he actively participates in program and organizing committees for prestigious international conferences, including World Conference on Smart Trends in Systems Security and Sustainability (WorldS4), International Congress on Information and Communication Technology (ICICT), International Conference on Information and Communications Technology for Sustainable Development (ICT4SD) etc.

He is also the Editor-in-Chief of International Journal of Ambient Computing and Intelligence, Associate Editor of IEEE Transactions on Technology and Society and series Co-Editor of Springer Tracts in Nature-Inspired Computing and Data-Intensive Research from Springer Nature and Advances in Ubiquitous Sensing Applications for Healthcare from Elsevier etc. Furthermore, he was an Editorial Board Member Complex & Intelligence Systems, Springer, Applied Soft Computing, Elsevier and he is an International Journal of Information Technology, Springer, International Journal of Information and Decision Sciences etc. He is a Fellow of IETE and member of IE, ISOC etc.

Duque, Carlos A.
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.