Biomedical Signal Analysis: A Case-Study Approach (Hardcover)
Rangaraj M. Rangayyan
- 出版商: Wiley
- 出版日期: 2001-12-21
- 售價: $1,200
- 貴賓價: 9.8 折 $1,176
- 語言: 英文
- 頁數: 552
- 裝訂: Hardcover
- ISBN: 0471208116
- ISBN-13: 9780471208112
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商品描述
An authoritative assessment of the problems and applications of biomedical
signals, rooted in practical case studies
The development of techniques to
analyze biomedical signals, such as electro-cardiograms, has dramatically
affected countless lives by making possible improved noninvasive diagnosis,
online monitoring of critically ill patients, and rehabilitation and sensory
aids for the handicapped. Rangaraj Rangayyan supplies a practical, hands-on
field guide to this constantly evolving technology in Biomedical Signal
Analysis, focusing on the diagnostic challenges that medical professionals
continue to face. Dr. Rangayyan applies a problem-solving approach to his study.
Each chapter begins with the statement of a different biomedical signal problem,
followed by a selection of real-life case studies and the associated signals.
Signal processing, modeling, or analysis techniques are then presented, starting
with relatively simple "textbook" methods, followed by more sophisticated
research approaches. The chapter concludes with one or more application
solutions; illustrations of real-life biomedical signals and their derivatives
are included throughout. Among the topics addressed are:
* Concurrent,
coupled, and correlated processes
* Filtering for removal of artifacts
*
Event detection and characterization
* Frequency-domain characterization
*
Modeling biomedical systems
* Analysis of nonstationary signals
* Pattern
classification and diagnostic decision
The chapters also present a number of
laboratory exercises, study questions, and problems to facilitate preparation
for class examinations and practical applications. Biomedical Signal Analysis
provides a definitive resource for upper-level under-graduate and graduate
engineering students, as well as for practicing engineers, computer scientists,
information technologists, medical physicists, and data processing specialists.