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020 _a9783030368449
_9978-3-030-36844-9
024 7 _a10.1007/978-3-030-36844-9
_2doi
050 4 _aR856-857
072 7 _aMQW
_2bicssc
072 7 _aTEC059000
_2bisacsh
072 7 _aMQW
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082 0 4 _a610.28
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245 1 0 _aSignal Processing in Medicine and Biology
_h[electronic resource] :
_bEmerging Trends in Research and Applications /
_cedited by Iyad Obeid, Ivan Selesnick, Joseph Picone.
250 _a1st ed. 2020.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2020.
300 _aVII, 281 p. 128 illus., 102 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
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505 0 _aChapter 1. An Analysis of Automated Parkinson’s Diagnosis Using Voice: Methodology and Future Directions -- Chapter 2. Noninvasive Vascular Blood Sound Monitoring Through Flexible Microphone -- Chapter 3. The Temple University Hospital Digital Pathology Corpus -- Chapter 4. Transient Artifacts Suppression in Time Series via Convex Analysis -- Chapter 5. The Hurst Exponent – A Novel Approach for Assessing Focus During Trauma Resuscitation -- Chapter 6. Gaussian Smoothing Filter For Improved EMG Signal Modeling -- Chapter 7. Clustering of SCG Events Using Unsupervised Machine Learning -- Chapter 8. Deep Learning Approaches for Automated Seizure Detection from Scalp Electroencephalograms.
520 _aThis 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. Covers traditional signal processing topics within biomedicine Promotes collaboration between healthcare practitioners and signal processing researchers Presents tutorials and examples of successful applications.
650 0 _aBiomedical engineering.
_93292
650 0 _aBiotechnology.
_97533
650 0 _aSignal processing.
_94052
650 0 _aMedical informatics.
_94729
650 0 _aRadiology.
_932514
650 1 4 _aBiomedical Engineering and Bioengineering.
_931842
650 2 4 _aBiotechnology.
_97533
650 2 4 _aSignal, Speech and Image Processing .
_931566
650 2 4 _aHealth Informatics.
_931799
650 2 4 _aRadiology.
_932514
700 1 _aObeid, Iyad.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_939370
700 1 _aSelesnick, Ivan.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_939371
700 1 _aPicone, Joseph.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_939372
710 2 _aSpringerLink (Online service)
_939373
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030368432
776 0 8 _iPrinted edition:
_z9783030368456
776 0 8 _iPrinted edition:
_z9783030368463
856 4 0 _uhttps://doi.org/10.1007/978-3-030-36844-9
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c76543
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