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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...

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...

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Related Experiment Video

Updated: Jun 20, 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

A robust wavelet-based multi-lead Electrocardiogram delineation algorithm.

A Ghaffari¹, M R Homaeinezhad, M Akraminia

¹Department of Mechanical Engineering, K.N. Toosi University of Technology, Tehran, Iran.

Medical Engineering & Physics

|August 21, 2009

Summary

This summary is machine-generated.

This study introduces a new algorithm using discrete wavelet transform (DWT) for accurate electrocardiogram (ECG) wave detection and delineation. The DWT-based method precisely identifies P-waves, QRS complexes, and T-waves, even with noisy signals.

Related Experiment Videos

Last Updated: Jun 20, 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

Area of Science:

Biomedical Engineering
Signal Processing
Cardiology

Background:

Accurate electrocardiogram (ECG) analysis is crucial for diagnosing cardiac conditions.
Existing ECG delineation algorithms face challenges with low signal-to-noise ratios and abnormal wave morphologies.

Purpose of the Study:

To develop a robust multi-lead ECG wave detection and delineation algorithm.
To accurately identify P-wave, QRS complex, and T-wave parameters using discrete wavelet transform (DWT).

Main Methods:

A novel algorithm based on discrete wavelet transform (DWT) was developed.
The method applies a simple approach to a selected DWT scale for wave detection and parameter estimation.
A variable thresholding criterion was designed for signal processing.

Main Results:

Achieved high sensitivity (Se=99.84%) and positive predictivity (P+=99.80%) for QRS complex detection.
Demonstrated low average delineation errors: 13.7ms (P-wave), 11.3ms (QRS), and 14.0ms (T-wave).
Showcased significant capability in handling low signal-to-noise ratios, baseline wander, and abnormal ECG morphologies.

Conclusions:

The developed DWT-based algorithm offers robust and accurate ECG wave detection and delineation.
The algorithm's performance was validated across multiple diverse ECG databases and clinical data.
This method shows promise for improved automated ECG interpretation in clinical settings.