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Biomedical Signal Processing

Innovation and Applications

Editors: Obeid, Iyad, Selesnick, Ivan, Picone, Joseph (Eds.)

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  • Presents an interdisciplinary look at research trends in signal processing and biomedicine
  • Promotes collaboration between healthcare practitioners and signal processing researchers
  • Includes tutorials and examples of successful applications
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eBook $84.99
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  • ISBN 978-3-030-67494-6
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  • Immediate eBook download after purchase
Hardcover $109.99
price for USA in USD
  • ISBN 978-3-030-67493-9
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
About this book

This book provides an interdisciplinary look at emerging trends in signal processing and biomedicine found at the intersection of healthcare, engineering, and computer science. It examines the vital role signal processing plays in enabling a new generation of technology based on big data, and looks at applications ranging from medical electronics to data mining of electronic medical records. Topics covered include analysis of medical images, machine learning, biomedical nanosensors, wireless technologies, and instrumentation and electrical stimulation. Biomedical Signal Processing: Innovation and Applications presents tutorials and examples of successful applications, and will appeal to a wide range of professionals, researchers, and students interested in applications of signal processing, medicine, and biology.

About the authors

Iyad Obeid, PhD, is an associate professor of Electrical and Computer Engineering at Temple University with a secondary appointment in the Department of Bioengineering. His research interests include neural signal processing, biomedical signal processing, and medical instrumentation. His research in these fields has been funded by NIH, NSF, DARPA, and the US Army. Together with Dr. Picone, he is the co-founder of the Neural Engineering Data Consortium, whose goal is to provide large, well curated neural signal data to the biomedical research community. In addition to earlier work on brain machine interfaces, Dr. Obeid’s current research has expanded to include non-parametric unsupervised machine learning as well as concussion and injury assessment instrumentation built using commercial off the shelf sensors.
Ivan Selesnick, PhD, is a professor of Electrical and Computer Engineering at NYU Tandon School of Engineering. He received the BS, MEE, and PhD degrees in Electrical Engineering from Rice University, and joined Polytechnic University in 1997 (now NYU Tandon School of Engineering). He received an Alexander von Humboldt Fellowship in 1997 and a National Science Foundation Career award in 1999. In 2003, he received the Jacobs Excellence in Education Award from Polytechnic University. Dr. Selesnick’s research interests are in signal and image processing, wavelet-based signal processing, sparsity techniques, and biomedical signal processing. He became an IEEE Fellow in 2016, and has been an associate editor for the IEEE Transactions on Image Processing, IEEE Signal Processing Letters, IEEE Transactions on Signal Processing, and IEEE Transactions on Computational Imaging.
Joseph Picone, PhD, is a professor of Electrical and Computer Engineering at Temple University, where he directs the Institute for Signal and Information Processing and is the Associate Director of the Neural Engineering Data Consortium. His primary expertise is in statistical modeling with applications in signal processing, specifically acoustic modeling in speech recognition. A common theme throughout his research career has been a focus on fundamentally new statistical modeling paradigms. He has been an active researcher in various aspects of speech processing for over 35 years. He currently collaborates with the Temple School of Medicine and has previously collaborated with many academic institutions (e.g., the Linguistic Data Consortium, Johns Hopkins), government agencies (e.g., Department of Defense, DARPA) and companies (e.g., MITRE, Texas Instruments). The National Science Foundation, DoD, DARPA and several commercial interests have funded his research. He has published over 200 technical papers and holds 8 patents.

Table of contents (8 chapters)

Table of contents (8 chapters)
  • Multi-class fNIRS Classification of Motor Execution Tasks with Application to Brain-Computer Interfaces

    Pages 1-32

    Shamsi, Foroogh (et al.)

  • A Comparative Study of End-To-End Discriminative Deep Learning Models for Knee Joint Kinematic Time Series Classification

    Pages 33-61

    Abid, M. (et al.)

  • Nonlinear Smoothing of Core Body Temperature Data with Random Gaps and Outliers (DRAGO)

    Pages 63-84

    Parekh, A. (et al.)

  • Wearable Smart Garment Devices for Passive Biomedical Monitoring

    Pages 85-128

    Amanatides, Chelsea (et al.)

  • Spatial Distribution of Seismocardiographic Signals

    Pages 129-159

    Azad, Md Khurshidul (et al.)

Buy this book

eBook $84.99
price for USA in USD
  • ISBN 978-3-030-67494-6
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $109.99
price for USA in USD
  • ISBN 978-3-030-67493-9
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
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Bibliographic Information

Bibliographic Information
Book Title
Biomedical Signal Processing
Book Subtitle
Innovation and Applications
Editors
  • Iyad Obeid
  • Ivan Selesnick
  • Joseph Picone
Copyright
2021
Publisher
Springer International Publishing
Copyright Holder
The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG
eBook ISBN
978-3-030-67494-6
DOI
10.1007/978-3-030-67494-6
Hardcover ISBN
978-3-030-67493-9
Edition Number
1
Number of Pages
VIII, 261
Number of Illustrations
35 b/w illustrations, 109 illustrations in colour
Topics