000 06044nam a2201177 i 4500
001 5264168
003 IEEE
005 20200421114114.0
006 m o d
007 cr |n|||||||||
008 100317t20152002njua ob 001 0 eng d
020 _a9780470544204
_qelectronic
020 _z9780470911396
_qprint
020 _z0471208116
_qpaper
020 _z9781601195708
_qebook
020 _z1601195702
_qebook
020 _z0470544201
_qelectronic
020 _z9780471208116
_qprint
024 7 _a10.1109/9780470544204
_2doi
035 _a(CaBNVSL)mat05264168
035 _a(IDAMS)0b000064810c405b
040 _aCaBNVSL
_beng
_erda
_cCaBNVSL
_dCaBNVSL
050 4 _aR857.S47
_bR365 2002eb
082 0 4 _a610/.28
_222
100 1 _aRangayyan, Rangaraj M.,
_eauthor.
245 1 0 _aBiomedical signal analysis :
_ba case-study approach /
_cRangaraj M. Rangayyan.
264 1 _a[Piscataway, New Jersey] :
_bIEEE Press,
_cc2002.
264 2 _a[Piscataqay, New Jersey] :
_bIEEE Xplore,
_c[2001]
300 _a1 PDF (xxxv, 516 pages) :
_billustrations.
336 _atext
_2rdacontent
337 _aelectronic
_2isbdmedia
338 _aonline resource
_2rdacarrier
490 1 _aIEEE press series on biomedical engineering ;
_v28
504 _aIncludes bibliographical references and index.
505 0 _aFront Matter -- Introduction to Biomedical Signals -- Concurrent, Coupled, and Correlated Processes -- Filtering for Removal of Artifacts -- Event Detection -- Analysis of Waveshape and Waveform Complexity -- Frequency-domain Characterization of Signals and Systems -- Modeling Biomedical Signalb2sgenerating Processes and Systems -- Analysis of Nonstationary Signals -- Pattern Classification and Diagnostic Decision -- References -- Index.
506 1 _aRestricted to subscribers or individual electronic text purchasers.
520 _aThe 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. An authoritative assessment of the problems and applications of biomedical signals, rooted in practical case studies An Instructor Support FTP site is available from the Wiley editorial department: ftp://ftp.ieee.org/uploads/press/rangayyan.
530 _aAlso available in print.
538 _aMode of access: World Wide Web
588 _aDescription based on PDF viewed 12/21/2015.
650 0 _aSignal processing.
650 0 _aBiomedical engineering.
655 0 _aElectronic books.
695 _aAnalytical models
695 _aArrays
695 _aBand pass filters
695 _aBibliographies
695 _aBiological system modeling
695 _aBiomedical measurements
695 _aBlood
695 _aBones
695 _aBrain modeling
695 _aComplexity theory
695 _aDelay
695 _aElectrocardiography
695 _aElectrodes
695 _aElectroencephalography
695 _aElectromyography
695 _aEvent detection
695 _aFeature extraction
695 _aFiltering
695 _aFiring
695 _aFrequency domain analysis
695 _aHeart
695 _aHeart rate variability
695 _aIndexes
695 _aInterference
695 _aIons
695 _aJoints
695 _aKnee
695 _aLead
695 _aMathematical model
695 _aMuscles
695 _aMyocardium
695 _aNoise
695 _aOsteoarthritis
695 _aPattern classification
695 _aPressure measurement
695 _aProbability density function
695 _aRandom processes
695 _aResonant frequency
695 _aRhythm
695 _aShape
695 _aSignal processing
695 _aSpeech
695 _aTemperature measurement
695 _aTemperature sensors
695 _aTime domain analysis
695 _aTime measurement
695 _aTransient analysis
695 _aTurning
695 _aValves
695 _aVisualization
695 _aWiener filter
710 2 _aJohn Wiley & Sons,
_epublisher.
710 2 _aIEEE Xplore (Online service),
_edistributor.
776 0 8 _iPrint version:
_z9780470911396
830 0 _aIEEE Press series in biomedical engineering ;
_v28
856 4 2 _3Abstract with links to resource
_uhttp://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=5264168
942 _cEBK
999 _c59457
_d59457