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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...

Electrocardiogram Fundamentals

Electrocardiogram Fundamentals

Introduction
An electrocardiogram (ECG) is a diagnostic tool for identifying cardiac conditions such as arrhythmias, conduction abnormalities, and myocardial ischemia.
Definition
An electrocardiogram (ECG) visualizes the heart's electrical activity by tracing the electrical movement associated with each heartbeat on a graph or monitor. As the heart beats, an electrical wave passes through it, correlating with the cardiac cycle events.
Parts of an ECG
An ECG utilizes electrodes on the skin...

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ECG Interpretation of Rhythms

An electrocardiogram (ECG)graphically represents the heart's electrical activity on ECG paper or a monitor.
Components of the Electrocardiogram
The primary components of a normal ECG waveform in Normal sinus rhythm(NSR) include the P wave, PR interval, QRS complex, ST segment, T wave, and occasionally a U wave.
ECG waveforms are divided by vertical and horizontal lines at standard intervals.
The horizontal axis measures time and rate, and the vertical axis measures amplitude or voltage....

Fetal Circulation

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Fetal circulation is a unique system that facilitates the exchange of gases, nutrients, and waste products between the developing fetus and the mother. This intricate process takes place through a special organ called the placenta.
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Related Experiment Video

Updated: Apr 26, 2026

Fetal Mouse Cardiovascular Imaging Using a High-frequency Ultrasound 30/45MHZ System

Fetal Mouse Cardiovascular Imaging Using a High-frequency Ultrasound 30/45MHZ System

Published on: May 5, 2018

An efficient unsupervised fetal QRS complex detection from abdominal maternal ECG.

M Varanini¹, G Tartarisco, L Billeci

¹Institute of Clinical Physiology, National Research Council, Pisa, Italy.

Physiological Measurement

|July 30, 2014

Summary

This study presents an unsupervised algorithm for non-invasive fetal electrocardiogram (fECG) analysis. The method effectively detects fetal heart rate by combining independent component analysis (ICA) and maternal ECG cancellation, achieving top scores in a major challenge.

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Related Experiment Videos

Last Updated: Apr 26, 2026

Fetal Mouse Cardiovascular Imaging Using a High-frequency Ultrasound 30/45MHZ System

Fetal Mouse Cardiovascular Imaging Using a High-frequency Ultrasound 30/45MHZ System

Published on: May 5, 2018

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice

Published on: May 23, 2021

Noninvasive Electrocardiography in the Perinatal Mouse

Noninvasive Electrocardiography in the Perinatal Mouse

Published on: June 12, 2020

Area of Science:

Biomedical Engineering
Signal Processing
Cardiology

Background:

Non-invasive fetal heart rate monitoring is crucial for assessing fetal well-being during pregnancy.
Analyzing abdominal fetal ECG presents challenges due to low signal-to-noise ratio and interference from maternal ECG, motion, and electromyographic artifacts.

Purpose of the Study:

To develop an efficient unsupervised algorithm for fetal QRS complex detection from multichannel abdominal recordings.
To improve the accuracy of fetal heart rate and interbeat interval estimation.

Main Methods:

Pre-processing to remove artifacts like baseline wander and power line interference.
Maternal ECG extraction and cancellation using Independent Component Analysis (ICA) and weighted Singular Value Decomposition (SVD).
Enhancement of fetal ECG signals through ICA and subsequent fetal QRS detection.

Main Results:

The developed algorithm achieved the top official scores in both event 1 and event 2 of the Physionet/Computing in Cardiology Challenge 2013.
The combined approach of ICA and maternal ECG cancellation outperformed individual methods.
The algorithm demonstrated superior performance in estimating fetal heart rate and interbeat intervals.

Conclusions:

The presented unsupervised algorithm offers an efficient and effective solution for non-invasive fetal ECG analysis.
The open-source release of the algorithms facilitates further research and clinical application.
This method significantly advances the capability to monitor fetal health non-invasively.