Literature DB >> 10694172

A novel wavelet transform based analysis reveals hidden structure in ventricular fibrillation.

J N Watson1, P S Addison, G R Clegg, M Holzer, F Sterz, C E Robertson.   

Abstract

We report a new method of interrogating the surface ECG signal using techniques developed in the field of wavelet transform analysis. Previously unreported structure within the ECG during ventricular fibrillation (VF) is found using a high-resolution decomposition of the signal employing the continuous wavelet transform. We believe that wavelet transform methods could lead to the development of powerful tools for use in the resuscitation of patients with cardiac arrest.

Entities:  

Mesh：

Year:  2000        PMID： 10694172     DOI： 10.1016/s0300-9572(99)00127-6

Source DB:  PubMed          Journal:  Resuscitation        ISSN： 0300-9572            Impact factor:   5.262


  9 in total

1.  Wavelet-based analysis of heart-rate-dependent ECG features.

Authors:  Martin K Stiles; David Clifton; Neil R Grubb; James N Watson; Paul S Addison
Journal:  Ann Noninvasive Electrocardiol       Date:  2004-10       Impact factor: 1.468

2.  An algorithm for the detection of individual breaths from the pulse oximeter waveform.

Authors:  Paul Leonard; Neil R Grubb; Paul S Addison; David Clifton; James N Watson
Journal:  J Clin Monit Comput       Date:  2004-12       Impact factor: 2.502

3.  A fully automated algorithm for the determination of respiratory rate from the photoplethysmogram.

Authors:  Paul A Leonard; J Graham Douglas; Neil R Grubb; David Clifton; Paul S Addison; James N Watson
Journal:  J Clin Monit Comput       Date:  2006-03-11       Impact factor: 2.502

4.  Ventricular Fibrillation Waveform Analysis During Chest Compressions to Predict Survival From Cardiac Arrest.

Authors:  Jason Coult; Jennifer Blackwood; Lawrence Sherman; Thomas D Rea; Peter J Kudenchuk; Heemun Kwok
Journal:  Circ Arrhythm Electrophysiol       Date:  2019-01

5.  Prompt prediction of successful defibrillation from 1-s ventricular fibrillation waveform in patients with out-of-hospital sudden cardiac arrest.

Authors:  Hiroshi Endoh; Seiji Hida; Satomi Oohashi; Yusuke Hayashi; Hidenori Kinoshita; Tadayuki Honda
Journal:  J Anesth       Date:  2010-11-27       Impact factor: 2.078

6.  Logarithm of the absolute correlations of the ECG waveform estimates duration of ventricular fibrillation and predicts successful defibrillation.

Authors:  Lawrence D Sherman; Thomas D Rea; James D Waters; James J Menegazzi; Clifton W Callaway
Journal:  Resuscitation       Date:  2008-07-01       Impact factor: 5.262

7.  A classification scheme for ventricular arrhythmias using wavelets analysis.

Authors:  K Balasundaram; S Masse; K Nair; K Umapathy
Journal:  Med Biol Eng Comput       Date:  2012-11-07       Impact factor: 2.602

8.  Quick identification of prostate cancer by wavelet transform-based photoacoustic power spectrum analysis.

Authors:  Shiying Wu; Ying Liu; Yingna Chen; Chengdang Xu; Panpan Chen; Mengjiao Zhang; Wanli Ye; Denglong Wu; Shengsong Huang; Qian Cheng
Journal:  Photoacoustics       Date:  2021-12-18

9.  Electrocardiogram frequency change by extracorporeal blood perfusion in a swine ventricular fibrillation model.

Authors:  Jung Chan Lee; Gil Joon Suh; Hee Chan Kim
Journal:  Biomed Eng Online       Date:  2013-11-25       Impact factor: 2.819
  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.