Academic Press Library in Biomedical Applications of Mobile and Wireless Communications: Wireless UWB Body Area Networks
Using the IEEE802.15.4-2011
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Wireless sensor and body area networks (WSN and WBAN respectively) have been seen as a future way to monitor humans’ psycho-physiological signs remotely. There are a number of standards that could be used for building WBAN sytems. However, wireless UWB networks based on IEEE 802.15.4a offer the advantages of a large frequency range and low power spectral density, making it suitable for both WSNs and WBANs used for medical applications. The technology has matured sufficiently that it can be used to develop products for the marketplace. This book presents how the IEEE802.15.4-2011 (former IEEE802.15.4a) can be used in wireless body area networks (WBAN) for healthcare and welfare related applications. It gives a short overview on the IEEE802.15.4 family and then gives details of IEEE802.15.4-2011 based solutions.
Key Features
- Presents how the IEEE802.15.4-2011 (former IEEE802.15.4a) can be used in wireless body area networks (WBAN) for healthcare and welfare related applications
- Gives a short overview on the IEEE802.15.4 family
- Gives details of IEEE802.15.4-2011 based solutions
Readership
Communications engineering field aimed at university researchers and R&D engineers in industry
Table of Contents
- List of Abbreviations and Variables
Acronyms
Variables
1. Introduction
1.1 IEEE802.15.4 Standard Family
2.1 Applications
3.1 The IEEE802.15.4-2011 Based UWB WBAN
4.1 WBAN Channels
5.1 Examples of Performance Analysis for Different Receiver Structures
6.1 Conclusion
References
Product details
- No. of pages: 48
- Language: English
- Copyright: © Academic Press 2014
- Published: March 5, 2014
- Imprint: Academic Press
- eBook ISBN: 9780128010020
About the Author
Matti Hämäläinen
Dr. Hämäläinen is Professor of Radiology at Massachusetts General hospital and Director of Magnetoencephalography (MEG) Core at Athinoula A. Martinos Center for Biomedical Imaging at MGH. He is one of the pioneers in the application of MEG in conjunction with other non-invasive functional and anatomical imaging methods to study human brain function. He has had a crucial role in developing whole-head MEG instrumentation, analytical methods and tools, as well as experimental protocols, which have together paved the way for MEG becoming an important basic research and clinical tool worldwide.
In 1993 he was the co-author of a seminal review article on MEG in Reviews of Modern Physics, now with more than 4000 citations. His current research interests include further development of anatomically-constrained MEG/EEG source estimation methods, including sparse and temporally continuous approaches, combination of non-invasive and invasive electromagnetic source imaging with hemodynamic measures, MEG/EEG studies of early brain development in infants, and adapting and extending MEG/EEG analysis methods to be applicable in real time in clinical neurophysiology studies.
Affiliations and Expertise
Professor of Radiology, Massachusetts General Hospital and Director of Magnetoencephalography (MEG) Core, Athinoula A. Martinos Center for Biomedical Imaging, MGH, Finland
About the Editor
Lorenzo Mucchi
Lorenzo Mucchi is an assistant professor at the Dept. of Information Engineering of the University of Florence, Italy, where he teaches Information Technologies. Lorenzo's main research areas include theoretical modelling, algorithms design and real measurements, mainly focused in the following fields: ultra wideband signals, localization and tracking, interference/channel modelling, intrinsic wireless security, adaptive diversity techniques and wireless healthcare. Lorenzo is senior member of the Institute of Electrical and Electronics Engineers (IEEE) and permanent member of the International Association of Science and Technology for Development (IASTED) Technical Committee on Telecommunications. All details are available at: http://lenst.det.unifi.it/~mucchi/
Affiliations and Expertise
Assistant professor at the Dept. of Information Engineering of the University of Florence, Italy.
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