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Journal Abstract Search

196 related items for PubMed ID: 16088063

  • 1. Assessment of ECG frequency and morphology parameters for automatic classification of life-threatening cardiac arrhythmias.
    Krasteva V, Jekova I.
    Physiol Meas; 2005 Oct; 26(5):707-23. PubMed ID: 16088063
    [Abstract] [Full Text] [Related]

  • 2. Sensitivity and specificity of an automated external defibrillator algorithm designed for pediatric patients.
    Atkins DL, Scott WA, Blaufox AD, Law IH, Dick M, Geheb F, Sobh J, Brewer JE.
    Resuscitation; 2008 Feb; 76(2):168-74. PubMed ID: 17765384
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  • 3. Bench study of the accuracy of a commercial AED arrhythmia analysis algorithm in the presence of electromagnetic interferences.
    Jekova I, Krasteva V, Ménétré S, Stoyanov T, Christov I, Fleischhackl R, Schmid JJ, Didon JP.
    Physiol Meas; 2009 Jul; 30(7):695-705. PubMed ID: 19525573
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  • 4. Comparative study of morphological and time-frequency ECG descriptors for heartbeat classification.
    Christov I, Gómez-Herrero G, Krasteva V, Jekova I, Gotchev A, Egiazarian K.
    Med Eng Phys; 2006 Nov; 28(9):876-87. PubMed ID: 16476566
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  • 5. Subtraction of 16.67 Hz railroad net interference from the electrocardiogram: application for automatic external defibrillators.
    Jekova I, Krasteva V.
    Physiol Meas; 2005 Dec; 26(6):987-1003. PubMed ID: 16311447
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  • 6. ECG spectral and morphological parameters reviewed and updated to detect adult and paediatric life-threatening arrhythmia.
    Aramendi E, Irusta U, Pastor E, Bodegas A, Benito F.
    Physiol Meas; 2010 Jun; 31(6):749-61. PubMed ID: 20410557
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  • 9. Feasibility of shock advice analysis during CPR through removal of CPR artefacts from the human ECG.
    Eilevstjønn J, Eftestøl T, Aase SO, Myklebust H, Husøy JH, Steen PA.
    Resuscitation; 2004 May; 61(2):131-41. PubMed ID: 15135189
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  • 10. Support vector machine-based arrhythmia classification using reduced features of heart rate variability signal.
    Asl BM, Setarehdan SK, Mohebbi M.
    Artif Intell Med; 2008 Sep; 44(1):51-64. PubMed ID: 18585905
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  • 11. An arrhythmia classification system based on the RR-interval signal.
    Tsipouras MG, Fotiadis DI, Sideris D.
    Artif Intell Med; 2005 Mar; 33(3):237-50. PubMed ID: 15811788
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  • 12. [Validation of a discontinuously recording, digital long-term ECG system (Siemens-Sirecust 802/850) using a single beat analysis].
    Zehender M, Meinertz T, Geibel A, Hohnloser S, Just H.
    Z Kardiol; 1989 Jan; 78(1):4-13. PubMed ID: 2466381
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  • 13. Enhancing the accuracy of shock advisory algorithms in automated external defibrillators during ongoing cardiopulmonary resuscitation using a cascade of CNNEDs.
    Nejad MPS, Kargin V, Hajeb-M S, Hicks D, Valentine M, Chon KH.
    Comput Biol Med; 2024 Apr; 172():108180. PubMed ID: 38452474
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  • 15. Automated detection of shockable and non-shockable arrhythmia using novel wavelet-based ECG features.
    Sharma M, Singh S, Kumar A, San Tan R, Acharya UR.
    Comput Biol Med; 2019 Dec; 115():103446. PubMed ID: 31627019
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  • 17. Robust neural-network-based classification of premature ventricular contractions using wavelet transform and timing interval features.
    Inan OT, Giovangrandi L, Kovacs GT.
    IEEE Trans Biomed Eng; 2006 Dec; 53(12 Pt 1):2507-15. PubMed ID: 17153208
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  • 20. Strong corruption of electrocardiograms caused by cardiopulmonary resuscitation reduces efficiency of two-channel methods for removing motion artefacts in non-shockable rhythms.
    Werther T, Klotz A, Granegger M, Baubin M, Feichtinger HG, Amann A, Gilly H.
    Resuscitation; 2009 Nov; 80(11):1301-7. PubMed ID: 19735967
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