Literature DB >> 3319381

Influence of noise on wave boundary recognition by ECG measurement programs. Recommendations for preprocessing.

J L Willems1, C Zywietz, P Arnaud, J H van Bemmel, R Degani, P W Macfarlane.   

Abstract

In the international cooperative project entitled "Common Standards for Quantitative Electrocardiography" (CSE) systematic noise tests have been performed in order to compare measurement results of electrocardiographic computer programs under degraded operational conditions and to develop recommendations for preprocessing and measurement strategies. The influence of seven different high- and low-frequency noise types on the recognition of P, QRS, and T wave onsets and offsets was investigated. The analysis was performed on 160 electrocardiograms derived from two sets of 10 cases each, by eight electrocardiographic and six vectorcardiographic computer programs. The stability and precision of these programs were tested with respect to the results obtained (1) in the noise-free recordings and (2) by a group of five cardiologists who have analyzed the recordings previously in a Delphi reviewing process. Increasing levels of high-frequency noise shifted the onsets and offsets of most programs outward. Programs analyzing an averaged beat showed significantly less variability than programs which measure every complex or a selected beat. On the basis of the findings of the present study, a measurement strategy based on selective averaging is recommended for diagnostic ECG computer programs. However, averaging should be performed only if proper alignment and precise waveform comparison have been performed beforehand in order to exclude dissimilar complexes.

Mesh:

Year:  1987        PMID: 3319381     DOI: 10.1016/0010-4809(87)90025-5

Source DB:  PubMed          Journal:  Comput Biomed Res        ISSN: 0010-4809


  5 in total

1.  Magnitude, mechanism, and reproducibility of QT interval differences between superimposed global and individual lead ECG complexes.

Authors:  Paul Kligfield; Benoit Tyl; Martine Maarek; Pierre Maison-Blanche
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2.  Methodology of QT-interval measurement in the modular ECG analysis system (MEANS).

Authors:  Jan A Kors; Gerard van Herpen
Journal:  Ann Noninvasive Electrocardiol       Date:  2009-01       Impact factor: 1.468

3.  Robust QT interval estimation--from algorithm to validation.

Authors:  Joel Q Xue
Journal:  Ann Noninvasive Electrocardiol       Date:  2009-01       Impact factor: 1.468

4.  Characteristic wave detection in ECG signal using morphological transform.

Authors:  Yan Sun; Kap Luk Chan; Shankar Muthu Krishnan
Journal:  BMC Cardiovasc Disord       Date:  2005-09-20       Impact factor: 2.298

5.  Discovering and Visualizing Disease-Specific Electrocardiogram Features Using Deep Learning: Proof-of-Concept in Phospholamban Gene Mutation Carriers.

Authors:  Rutger R van de Leur; Karim Taha; Max N Bos; Jeroen F van der Heijden; Deepak Gupta; Maarten J Cramer; Rutger J Hassink; Pim van der Harst; Pieter A Doevendans; Folkert W Asselbergs; René van Es
Journal:  Circ Arrhythm Electrophysiol       Date:  2021-01-05
  5 in total

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