Placement of ECG leads

2014 ◽  
Author(s):  
Tessa Davis
Keyword(s):  
Ecg Leads

Methodology of ECG Interpretation in the AVA Program

1990 ◽  
Vol 29 (04) ◽  
pp. 337-340 ◽  
Author(s):  
H. A. Pipberger ◽  
H. V. Pipberger ◽  
C. D. McManus
Keyword(s):  
Right Atrial ◽  
Signal Recognition ◽  
Multivariate Statistical ◽  
Reference Base ◽  
T Wave ◽  
Electrolyte Disturbances ◽  
Ecg Criteria ◽  
Wall Injury ◽  
Ecg Leads ◽  
Diagnostic Module

AbstractThe AVA program combines a thirty-year history with an approach that remains innovative; namely: multivariate statistical analysis on orthogonal ECG leads. Its diagnostic reference base includes only diagnoses independently verified by non-ECG criteria. The diagnostic module assesses probabilities of nine alternative disease categories, based on QRS-T parameters; or four other categories in case of conduction defects. Probabilities of left or right atrial overload are also computed. The program also recognizes wall injury, T-wave abnormalities, electrolyte disturbances, myocardial ischemia, and makes differential diagnoses between strain and digitalis effects. An arrhythmia classification module can generate any of 40 rhythm statements. Signal recognition is based on the spatial velocity function. The program has been translated to a microcomputer version.

scholarly journals Electrocardiogram lead selection for intelligent screening of patients with systolic heart failure

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yu-An Chiou ◽  
Jhen-Yang Syu ◽  
Sz-Ying Wu ◽  
Lian-Yu Lin ◽  
Li Tzu Yi ◽  
...  
Keyword(s):  
Heart Failure ◽  
Low Cost ◽  
Screening Method ◽  
Systolic Heart Failure ◽  
Rapid Screening ◽  
Ecg Signals ◽  
Testing Dataset ◽  
Lead Selection ◽  
Ecg Leads ◽  
Intelligent Screening

AbstractElectrocardiogram (ECG)-based intelligent screening for systolic heart failure (HF) is an emerging method that could become a low-cost and rapid screening tool for early diagnosis of the disease before the comprehensive echocardiographic procedure. We collected 12-lead ECG signals from 900 systolic HF patients (ejection fraction, EF < 50%) and 900 individuals with normal EF in the absence of HF symptoms. The 12-lead ECG signals were converted by continuous wavelet transform (CWT) to 2D spectra and classified using a 2D convolutional neural network (CNN). The 2D CWT spectra of 12-lead ECG signals were trained separately in 12 identical 2D-CNN models. The 12-lead classification results of the 2D-CNN model revealed that Lead V6 had the highest accuracy (0.93), sensitivity (0.97), specificity (0.89), and f1 scores (0.94) in the testing dataset. We designed four comprehensive scoring methods to integrate the 12-lead classification results into a key diagnostic index. The highest quality result among these four methods was obtained when Leads V5 and V6 of the 12-lead ECG signals were combined. Our new 12-lead ECG signal–based intelligent screening method using straightforward combination of ECG leads provides a fast and accurate approach for pre-screening for systolic HF.

scholarly journals Quantitative Approach to Fragmented QRS in Arrhythmogenic Cardiomyopathy: From Disease towards Asymptomatic Carriers of Pathogenic Variants

2020 ◽  
Vol 9 (2) ◽  
pp. 545 ◽  
Author(s):  
Rob W. Roudijk ◽  
Laurens P. Bosman ◽  
Jeroen F. van der Heijden ◽  
Jacques M. T. de Bakker ◽  
Richard N. W. Hauer ◽  
...  
Keyword(s):  
Early Stage ◽  
Pathogenic Variant ◽  
Observer Agreement ◽  
Arrhythmogenic Cardiomyopathy ◽  
Fragmented Qrs ◽  
Early Disease Detection ◽  
Pathogenic Variants ◽  
Disease Penetrance ◽  
Ecg Leads ◽  
And Control

Fragmented QRS complexes (fQRS) are common in patients with arrhythmogenic cardiomyopathy (ACM). A new method of fQRS quantification may aid early disease detection in pathogenic variant carriers and assessment of prognosis in patients with early stage ACM. Patients with definite ACM (n = 221, 66%), carriers of a pathogenic ACM-associated variant without a definite ACM diagnosis (n = 57, 17%) and control subjects (n = 58, 17%) were included. Quantitative fQRS (Q-fQRS) was defined as the total amount of deflections in the QRS complex in all 12 electrocardiography (ECG) leads. Q-fQRS was scored by a single observer and reproducibility was determined by three independent observers. Q-fQRS count was feasible with acceptable intra- and inter-observer agreement. Q-fQRS count is significantly higher in patients with definite ACM (54 ± 15) and pathogenic variant carriers (55 ± 10) compared to controls (35 ± 5) (p < 0.001). In patients with ACM, Q-fQRS was not associated with sustained ventricular arrhythmia (p = 0.701) at baseline or during follow-up (p = 0.335). Both definite ACM patients and pathogenic variant carriers not fulfilling ACM diagnosis have a higher Q-fQRS than controls. This may indicate that increased Q-fQRS is an early sign of disease penetrance. In concealed and early stages of ACM the role of Q-fQRS for risk stratification is limited.

Absence of ST elevation in ECG leads V7, V8, V9 in ischaemia of non-occlusive aetiologies

2004 ◽  
Vol 97 (3) ◽  
pp. 389-392 ◽  
Author(s):  
Kian-Keong Poh ◽  
Boon-Lock Chia ◽  
Huay-Cheem Tan ◽  
Tiong-Cheng Yeo ◽  
Yean-Teng Lim
Keyword(s):  
St Elevation ◽  
Ecg Leads

How Do Cardiology Practitioners Interpret an Electrocardiogram: An Eye Tracking Study (Preprint)

2021 ◽  
Author(s):  
Mohammed Tahri Sqalli ◽  
Dena Al-Thani ◽  
Mohamed Badreldin Elshazly ◽  
Mohammed Ahmad Al-Hijji ◽  
Yahya Sqalli Houssaini
Keyword(s):  
Standard Deviation ◽  
Medical Students ◽  
Eye Tracking ◽  
Practical Experience ◽  
Healthcare Sector ◽  
Visual Expertise ◽  
Medical Practitioners ◽  
Eye Fixations ◽  
Expertise Level ◽  
Ecg Leads

BACKGROUND Visual expertise refers to advanced visual skills demonstrated when executing domain‐specific visual tasks. Understanding healthcare practitioners’ visual expertise across different levels in the healthcare sector is crucial in clarifying how to acquire accurate interpretations of electrocardiograms (ECGs). OBJECTIVE The study aims to quantify, through the use of eye-tracking, differences in the visual expertise of medical practitioners, such as medical students, cardiology nurses, technicians, fellows, and consultants, when interpreting ECGs. METHODS Sixty-three participants with different healthcare roles participated in an eye-tracking study that consisted of interpreting 10 ECGs with different heart abnormalities. A counterbalanced within-subjects design was employed with one independent variable consisting of the expertise level of the medical practitioners and two measured eye-tracking dependent variables (fixations count and fixations revisitation). Eye-tracking data was assessed according to the accuracy of interpretation and frequency interpreters visited different leads in ECGs. In addition, the median and standard deviation in the interquartile range for the fixations count and the mean and standard deviation for the ECG lead revisitations were calculated. RESULTS Accuracy of interpretation ranged between 98% among consultants and 52% among medical students. Eye-tracking features also reflected this difference in the accuracy of interpretation. The results of the eye fixations count and eye fixations revisitations indicate that the less experienced medical practitioners need to observe various ECG leads more carefully. However, experienced medical practitioners rely on visual pattern recognition to provide their ECG diagnoses. CONCLUSIONS The results show that visual expertise for ECG interpretation is linked to the practitioner’s role within the healthcare system and the number of years of practical experience interpreting ECGs. Medical practitioners focus on different ECG leads and different waveform abnormalities according to their role in the healthcare sector and their expertise levels.

ECG LEADS

1963 ◽  
Vol 24 (3) ◽  
pp. 417-417
Keyword(s):  
Ecg Leads

scholarly journals Common ECG Lead Placement Errors. Part II: Precordial Misplacements

2014 ◽  
Vol 2 (3) ◽  
pp. 99-103 ◽  
Author(s):  
Allison V. Rosen ◽  
Sahil Koppikar ◽  
Catherine Shaw ◽  
Adrian Baranchuk
Keyword(s):  
Healthy Subject ◽  
Patient Care ◽  
Diagnostic Tool ◽  
Pathological Findings ◽  
Precordial Lead ◽  
Single Male ◽  
Lead Placement ◽  
Optimal Patient Care ◽  
Ecg Leads ◽  
Ecg Interpretation

Background: Electrocardiography is a very useful diagnostic tool. However, errors in placement of ECG leads can create artifacts, mimic pathologies, and hinder proper ECG interpretation. This is the second of a two-part series discussing how to recognize and avoid these errors. Methods: 12-lead ECGs were recorded in a single male healthy subject in his mid 20s. Various precordial lead misplacements were compared to ECG recordings from correct lead placement. Results: Precordial misplacements caused classical changes in ECG patterns. Techniques of differentiating these ECG patterns from true pathological findings were described. Conclusion: As in Part I of this series, recognition and interpretation of common ECG placement errors is critical in providing optimal patient care.

scholarly journals Heart Rate Dependency and Inter-Lead Variability of the T Peak – T End Intervals

2020 ◽  
Vol 11 ◽  
Author(s):  
Irena Andršová ◽  
Katerina Hnatkova ◽  
Martina Šišáková ◽  
Ondřej Toman ◽  
Peter Smetana ◽  
...  
Keyword(s):  
Heart Rate ◽  
Three Dimensional ◽  
Rate Dependency ◽  
Rate Dependent ◽  
Heart Rate Correction ◽  
Ecg Leads ◽  
Relationship Of ◽  
The Relationship ◽  
Vector Magnitude

The electrocardiographic (ECG) assessment of the T peak–T end (Tpe) intervals has been used in many clinical studies, but several related physiological aspects have not been reported. Specifically, the sources of the Tpe differences between different ECG leads have not been systematically researched, the relationship of Tpe duration to underlying heart rate has not been firmly established, and little is known about the mutual correspondence of Tpe intervals measured in different ECG leads. This study evaluated 796,620 10-s 12-lead ECGs obtained from long-term Holters recorded in 639 healthy subjects (311 female) aged 33.8 ± 9.4 years. For each ECG, transformation to orthogonal XYZ lead was used to measure Tpe in the orthogonal vector magnitude (used as a reference for lead-to-lead comparisons) and to construct a three-dimensional T wave loop. The loop roundness was expressed by a ratio between its circumference and length. These ratios were significantly related to the standard deviation of Tpe durations in different ECG leads. At the underlying heart rate of 60 beats per minute, Tpe intervals were shorter in female than in male individuals (82.5 ± 5.6 vs 90.0 ± 6.5 ms, p &lt; 0.0001). When studying linear slopes between Tpe intervals measured in different leads and the underlying heart rate, we found only minimal heart rate dependency, which was not systematic across the ECG leads and/or across the population. For any ECG lead, positive Tpe/RR slope was found in some subjects (e.g., 79 and 25% of subjects for V2 and V4 measurements, respectively) and a negative Tpe/RR slope in other subjects (e.g., 40 and 65% for V6 and V5, respectively). The steepest positive and negative Tpe/RR slopes were found for measurements in lead V2 and V4, respectively. In all leads, the Tpe/RR slope values were close to zero, indicating, on average, Tpe changes well below 2 ms for RR interval changes of 100 ms. On average, longest Tpe intervals were measured in lead V2, the shortest in lead III. The study concludes that the Tpe intervals measured in different leads cannot be combined. Irrespective of the measured ECG lead, the Tpe interval is not systematically heart rate dependent, and no heart rate correction should be used in clinical Tpe investigations.

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