2018 Computing in Cardiology Conference (CinC) 2018
DOI: 10.22489/cinc.2018.100
|View full text |Cite
|
Sign up to set email alerts
|

Detection of Unicolor ECG Electrode Reversals in Standard 12-Lead ECG

Abstract: This paper presents the performance of a commercial lead quality monitoring library (LQMLib, Schiller AG) for detection of reversals between 12-lead ECG cables with matching colors and proposes methods for improvements, where necessary. The study is performed on a large 12-lead ECG database with 1331 chest pain patients (646 training, 685 test recordings) and ECGs from 29 volunteers with swapped red, yellow, green, black and all unicolor cables. Relying on assessment of inter-lead correlations over continuous … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
5

Citation Types

0
6
0

Year Published

2019
2019
2024
2024

Publication Types

Select...
4

Relationship

0
4

Authors

Journals

citations
Cited by 4 publications
(6 citation statements)
references
References 13 publications
(19 reference statements)
0
6
0
Order By: Relevance
“…In Rjoob et al (2019aRjoob et al ( , 2019b, authors conducted V1 and V2 misplacement detection in three different positions: first, second and third intercostal spaces, which was based on morphological, frequency, and statistical features. Lead correlation features calculate correlation coefficients between leads and use machine learning models to detect misplacement based on coefficient trends (Jekova et al 2013, Jekova et al 2016, Jekova et al 2018. Lead redundancy information utilized the fact that limb leads can be reconstructed through any two limb leads, and changes in the correlation coefficients of the reconstructed leads can be used to detect misplacement (Kors and van Herpen 2001).…”
Section: Introductionmentioning
confidence: 99%
“…In Rjoob et al (2019aRjoob et al ( , 2019b, authors conducted V1 and V2 misplacement detection in three different positions: first, second and third intercostal spaces, which was based on morphological, frequency, and statistical features. Lead correlation features calculate correlation coefficients between leads and use machine learning models to detect misplacement based on coefficient trends (Jekova et al 2013, Jekova et al 2016, Jekova et al 2018. Lead redundancy information utilized the fact that limb leads can be reconstructed through any two limb leads, and changes in the correlation coefficients of the reconstructed leads can be used to detect misplacement (Kors and van Herpen 2001).…”
Section: Introductionmentioning
confidence: 99%
“…Generally, when another precordial lead is substituted for V1, the result is a tall R wave in V1, which could be taken as a sign of right bundle branch block, left ventricular ectopy, right ventricular hypertrophy, acute right ventricular dilation, Type A Wolff-Parkinson-White syndrome, posterior MI, hypertrophic cardiomyopathy, progressive muscular dystrophy or dextrocardia [10]. Reversals between limb and chest electrodes are a possible scenario due to the matching colors of the two ECG cables [11] or the incorrect attachment of the cable connectors to the junction box of the ECG machine [12]. C2/LA (yellow) cable interchange is described in two case reports [13,14] to have produced right axis deviation and Q waves in (III, aVF), accompanied by an inverted T wave in both leads, together with a quick transition in V2 with qR complex and an inverted T wave.…”
Section: Introductionmentioning
confidence: 99%
“…Reversals between limb and chest electrodes are a possible scenario due to the matching colors of the two ECG cables [11] or the incorrect attachment of the cable connectors to the junction box of the ECG machine [12]. C2/LA (yellow) cable interchange is described in two case reports [13,14] to have produced right axis deviation and Q waves in (III, aVF), accompanied by an inverted T wave in both leads, together with a quick transition in V2 with qR complex and an inverted T wave.…”
Section: Introductionmentioning
confidence: 99%
See 2 more Smart Citations