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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...

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...

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...

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...

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Related Experiment Video

Updated: Jul 15, 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

ECG beat detection using a geometrical matching approach.

Kleydis V Suárez¹, Jesus C Silva, Yannick Berthoumieu

¹LAPS, University of Bordeaux I, 351-cours de la Libération, 33405 Talence, France. kleydis.suarez@laps.ims-bordeaux.fr

IEEE Transactions on Bio-Medical Engineering

|April 5, 2007

Summary

This study introduces a novel geometrical matching method for R-wave detection in electrocardiography (ECG) signals. The approach achieves high accuracy in identifying heartbeat events using polynomial models and genetic algorithms.

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Area of Science:

Biomedical Engineering
Signal Processing
Cardiology

Background:

Electrocardiography (ECG) is crucial for diagnosing cardiac conditions.
Accurate R-wave detection is fundamental for analyzing ECG signals and identifying arrhythmias.
Existing R-wave detection methods face challenges with signal variability and noise.

Purpose of the Study:

To develop an original approach for identifying heartbeat morphologies and detecting R-wave events in ECG signals.
To introduce a "geometrical matching" rule for robust R-wave detection.
To evaluate the performance of the proposed method using a standard arrhythmia database.

Main Methods:

A "geometrical matching" rule is employed within a local moving-window procedure.
A decision function, based on a normalized similarity criterion, compares input ECG segments to a reference beat pattern in a nonlinear-curve space.
The reference pattern is modeled using polynomial expansion, and an algebraic-fitting distance is defined in the curve space. Genetic algorithms are used for training the decision function, followed by a level-detection algorithm for R-wave detection.
The method operates in two stages: training using genetic algorithms and detection using a level-detection algorithm.

Main Results:

The proposed geometrical matching approach achieved approximately 98% sensitivity for R-wave detection.
Positive predictivity for R-wave detection reached approximately 99%.
The method demonstrated effectiveness using low-order polynomial models on the MIT-BIH Arrhythmia Database.

Conclusions:

The developed geometrical matching approach offers a highly accurate and reliable method for R-wave detection in ECG signals.
The use of polynomial models and genetic algorithms provides an effective framework for heartbeat analysis.
This technique holds promise for improving automated cardiac arrhythmia diagnosis.