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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...

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...

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...

Instrumentation Amplifier

Instrumentation Amplifier

An electrocardiography (ECG) machine is an essential piece of medical equipment used to monitor the electrical activity of the heart. It operates by detecting small electrical changes on the skin that result from the depolarization of the heart muscle during each heartbeat. However, these signals are in the microvolt range and can be easily overwhelmed by noise or interference.
To overcome this challenge, an ECG machine utilizes an instrumentation amplifier. This specialized amplifier is...

ECG Interpretation of Arrhythmias II: Atrial, Junctional and Ventricular Arrhythmias

ECG Interpretation of Arrhythmias II: Atrial, Junctional and Ventricular Arrhythmias

Arrhythmia is a condition characterized by an irregular heart rhythm, with ECG changes that differ based on its origin and nature. The types of arrhythmias discussed below include atrial, junctional, and ventricular arrhythmias.Atrial ArrhythmiasPremature Atrial Complexes (PACs): PACs are early atrial beats caused by stress, caffeine, alcohol, electrolyte imbalances, hypoxia, hyperthyroidism, or certain medications (e.g., bronchodilators and decongestants). The ECG shows early P waves with an...

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Related Experiment Video

Updated: Jun 26, 2026

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

Improving ECG beats delineation with an evolutionary optimization process.

Jerome Dumont Ast¹, Alfredo I Hernández, Guy Carrault

¹INSERM, U642, Université de Rennes 1, Rennes, France. jerome.dumont@univ-rennes1.fr

IEEE Transactions on Bio-Medical Engineering

|January 28, 2009

Summary

This study introduces an automated method using evolutionary algorithms to optimize parameters for electrocardiogram (ECG) delineation. The new approach significantly improves ECG analysis accuracy compared to existing methods.

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Last Updated: Jun 26, 2026

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice

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Published on: May 23, 2021

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System

Published on: April 11, 2025

Area of Science:

Biomedical Signal Processing
Computational Intelligence
Cardiovascular Monitoring

Background:

Electrocardiogram (ECG) beat delineation involves complex signal processing modules with numerous parameters.
Manual, empirical parameter adjustment is time-consuming and relies heavily on designer expertise.
Optimizing these parameters is crucial for accurate ECG analysis.

Purpose of the Study:

To propose a novel automated and quantitative method for optimizing signal processing algorithm parameters.
To apply an evolutionary algorithm (EA) for multiobjective parameter optimization in ECG delineation.
To enhance the performance of a wavelet-transform-based ECG delineator.

Main Methods:

An evolutionary algorithm (EA) was employed to address the multiobjective optimization problem of parameter tuning.
The EA-based optimization was applied to a wavelet-transform-based ECG delineator.
Performance evaluation was conducted on the Physionet QT database, comparing results with existing literature.

Main Results:

The optimized parameters resulted in a more accurate ECG delineation.
A global improvement of 7.7% was achieved across all evaluated criteria.
The proposed method outperformed previously reported algorithms in ECG delineation accuracy.

Conclusions:

The automated, EA-based parameter optimization offers a significant advancement in ECG signal processing.
This quantitative approach provides a more accurate and efficient method for ECG beat delineation.
The findings demonstrate the potential of evolutionary algorithms for optimizing complex biomedical signal processing tasks.