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Electrocardiogram

Electrocardiogram

An electrocardiogram (ECG or EKG) is a critical diagnostic tool that records the electrical signals produced by the heart during each heartbeat. This recording is achieved through electrodes placed strategically on the arms, legs, and chest. The electrocardiograph amplifies these signals and produces 12 distinct tracings, offering a comprehensive understanding of the heart's electrical activity.
Three major waveforms are present in a typical ECG recording: the P wave, the QRS complex, and...

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Related Experiment Video

Updated: May 23, 2025

Preclinical Cardiac Electrophysiology Assessment by Dual Voltage and Calcium Optical Mapping of Human Organotypic Cardiac Slices

Preclinical Cardiac Electrophysiology Assessment by Dual Voltage and Calcium Optical Mapping of Human Organotypic Cardiac Slices

Published on: June 16, 2020

Quantifying anatomically-based in-silico electrocardiogram variability for cardiac digital twins.

Elena Zappon¹, Matthias A F Gsell¹, Karli Gillette²

¹Division of Biophysics and Medical Physics, Gottfried Schatz Research Center, Medical University of Graz, Graz, Austria.

Computers in Biology and Medicine

|March 9, 2025

Summary

This summary is machine-generated.

Cardiac digital twins (CDTs) are reliable for patient heart simulation. Uncertainties in data and model creation do not significantly impact electrocardiogram (ECG) diagnostic markers, ensuring accurate calibration.

Keywords:

Anatomical uncertainty Beat-to-beat variability Computational cardiology Electrocardiograms Lead placement uncertainty

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Last Updated: May 23, 2025

Preclinical Cardiac Electrophysiology Assessment by Dual Voltage and Calcium Optical Mapping of Human Organotypic Cardiac Slices

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Published on: June 16, 2020

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Published on: January 8, 2013

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Published on: April 11, 2025

Area of Science:

Computational modeling
Biophysics
Medical imaging

Background:

Human cardiac digital twins (CDTs) are patient-specific heart replicas.
Electrocardiogram (ECG) is used for calibrating CDTs.
Clinical data and CDT generation have inherent uncertainties.

Purpose of the Study:

Analyze the impact of uncertainties on ECG morphology and diagnostic markers.
Assess the reliability of ECG-based CDT calibration.
Investigate the resilience of CDT calibration to data variability.

Main Methods:

Utilized a biophysically detailed whole-heart EP model and torso model.
Varied anatomical factors, electrical conductivities, and electrode placements.
Analyzed residual beat-to-beat variability in ECG from healthy and patient datasets.

Main Results:

Diagnostic ECG features and morphology remained consistent despite uncertainties.
ECG morphology showed resilience to variations in heart location, size, orientation, and conductivity.
Observed narrow ECG distributions due to beat-to-beat variability.

Conclusions:

Observation uncertainties do not hinder accurate CDT calibration.
ECG-based CDT calibration is reliable for clinical electrophysiology.
CDTs can be accurately calibrated even with inherent data acquisition variability.