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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 the T...

ECG Interpretation of Rhythms

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. When...

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 to...

Correlation between ECG and Cardiac Cycle

Correlation between ECG and Cardiac Cycle

The electrical signals recorded on an electrocardiogram (ECG) occur before the mechanical processes of contraction and relaxation during the cardiac cycle.
A cardiac action potential originates in the SA node and spreads throughout the atria and the AV node in approximately 0.03 seconds. This results in the P wave in an ECG and triggers atrial contraction. The action potential is then briefly slowed at the AV node, allowing the atria to contract and fill the ventricles with blood before...

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Related Experiment Video

Updated: Jun 6, 2026

Electrophysiological Analysis of human Pluripotent Stem Cell-derived Cardiomyocytes (hPSC-CMs) Using Multi-electrode Arrays (MEAs)

Electrophysiological Analysis of human Pluripotent Stem Cell-derived Cardiomyocytes (hPSC-CMs) Using Multi-electrode Arrays (MEAs)

Published on: May 12, 2017

Foetal PQRST extraction from ECG recordings using cyclostationarity-based source separation method.

Michel Haritopoulos¹, Cécile Capdessus, Asoke K Nandi

¹Institut PRISME, 21, rue de Loigny la Bataille, 28000, Chartres, France. Michel.Haritopoulos@univ-orleans.fr

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|November 25, 2010

Summary

This study introduces a new method for extracting fetal electrocardiogram (FECG) signals from maternal recordings using cyclostationary properties. The approach effectively isolates FECG components without needing prior PQRST complex information.

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Area of Science:

Biomedical Engineering
Signal Processing
Maternal-Fetal Medicine

Background:

Fetal electrocardiogram (FECG) extraction from maternal ECG is challenging due to signal overlap.
Existing methods often require prior knowledge of fetal heart signal characteristics.

Purpose of the Study:

To develop a novel FECG extraction method utilizing signal cyclostationary properties.
To address the limitations of current FECG extraction techniques.

Main Methods:

Employing a blind source separation (BSS) framework tailored for FECG.
Leveraging the unique statistical (cyclostationary) properties of the target FECG signal.
Estimating FECG contributions without prior PQRST feature knowledge.

Main Results:

The proposed method successfully estimates FECG signals, including PQRST complexes.
Demonstrated effective FECG extraction even when maternal ECG is predominant.
Validated the algorithm's ability to identify FECG without specific feature templates.

Conclusions:

The cyclostationary-based BSS approach offers a robust solution for FECG extraction.
This method provides accurate FECG estimates, paving the way for improved fetal monitoring.
Opens possibilities for advanced fetal heart rate variability (HRV) analysis.