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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.
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.
This book covers emerging trends in signal processing research and
biomedical engineering, exploring the ways in which signal
processing plays a vital role in applications ranging from medical
electronics to data mining of electronic medical records. Topics
covered include statistical modeling of electroencephalograph data
for predicting or detecting seizure, stroke, or Parkinson's;
machine learning methods and their application to biomedical
problems, which is often poorly understood, even within the
scientific community; signal analysis; medical imaging; and machine
learning, data mining, and classification. The book features
tutorials and examples of successful applications that will appeal
to a wide range of professionals and researchers interested in
applications of signal processing, medicine, and biology.
This book provides an interdisciplinary look at emerging trends in
signal processing and biomedicine found at the intersection of
healthcare, engineering, and computer science. Bringing together
expanded versions of selected papers presented at the 2020 IEEE
Signal Processing in Medicine and Biology Symposium (IEEE SPMB), 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 Sensing and Analysis: Signal Processing in Medicine and
Biology 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. 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.
Signal Processing in Medicine and Biology: Innovations in Big Data
Processing provides an interdisciplinary look at state-of-the-art
innovations in biomedical signal processing, especially as it
applies to large data sets and machine learning. Chapters are
presented with detailed mathematics and complete implementation
specifics so that readers can completely master these techniques.
The book 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 at the intersection between healthcare, engineering,
and computer science.
This book provides an interdisciplinary look at emerging trends in
signal processing and biomedicine found at the intersection of
healthcare, engineering, and computer science. Bringing together
expanded versions of selected papers presented at the 2020 IEEE
Signal Processing in Medicine and Biology Symposium (IEEE SPMB), 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 Sensing and Analysis: Signal Processing in Medicine and
Biology 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. 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.
"Signals: Continuous and Discrete" is a practical, student-friendly
textbook for introductory courses in signal processing. This
textbook covers the material in a straightforward, easily
digestible manner by focusing on the most critical information and
developing an intuitive understanding of the underlying
mathematics.
Topics covered in the text include the Fourier series, the Fourier
transform, systems and signals, pole-zero theory, convolution,
sampling, and digital signal processing.
Successfully classroom tested, "Signals: Continuous and Discrete"
is a clear, concise textbook for upper division students and an
excellent reference for graduate students or professionals in
industry.
Iyad Obeid is a professor of electrical and computer engineering at
Temple University. Dr. Obeid holds a Ph.D. in biomedical
engineering from Duke University. His research focuses on neural
interfaces and biomedical signal acquisition and processing. He is
the author of numerous professional publications and is a member of
the IEEE.
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