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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...

Pulse rhythm

Pulse rhythm

Pulse rhythm refers to the pattern of pulsations within specific intervals, offering valuable insights into the regularity or irregularity of the heart's beats as observed through the pattern of pulsation within specific intervals. A regular pulse exhibits a consistent heart rate with uniform waveforms and pulsation force, variations of which can be classified as normal, weak, or bounding.
Conversely, an irregular pulse pattern is termed dysrhythmia, stemming from disruptions in cardiac muscle...

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...

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

BrainBeats as an Open-Source EEGLAB Plugin to Jointly Analyze EEG and Cardiovascular Signals

BrainBeats as an Open-Source EEGLAB Plugin to Jointly Analyze EEG and Cardiovascular Signals

Published on: April 26, 2024

High efficient system for automatic classification of the electrocardiogram beats.

Ataollah Ebrahim Zadeh¹, Ali Khazaee

¹Faculty of Electrical and Computer Engineering, Babol University of Technology, Shariati Blvd., Babol, Iran. e_zadeh@nit.ac.ir

Annals of Biomedical Engineering

|December 9, 2010

Summary

This summary is machine-generated.

This study presents an efficient system for classifying electrocardiogram (ECG) signals, identifying normal heartbeats and four types of arrhythmia. Optimization using a genetic algorithm significantly improved classification accuracy, making the hybrid intelligent system superior.

Related Experiment Videos

Last Updated: Jun 6, 2026

BrainBeats as an Open-Source EEGLAB Plugin to Jointly Analyze EEG and Cardiovascular Signals

BrainBeats as an Open-Source EEGLAB Plugin to Jointly Analyze EEG and Cardiovascular Signals

Published on: April 26, 2024

Area of Science:

Biomedical Engineering
Cardiology
Signal Processing

Background:

Accurate electrocardiogram (ECG) signal classification is crucial for diagnosing heart disease.
Existing systems often require manual parameter tuning, impacting efficiency and accuracy.

Purpose of the Study:

To design a high-efficiency system for classifying five types of ECG beats, including normal and four arrhythmia types.
To compare a system with optimized parameters against one with fixed parameters for improved ECG analysis.

Main Methods:

Feature extraction using Discrete Wavelet Transform for morphological and timing features.
Classification using a multi-class Support Vector Machine (SVM).
A novel Hybrid Intelligent System (HIS) incorporating a genetic algorithm for optimizing wavelet filters, decomposition levels, and SVM parameters.

Main Results:

Extensive experiments highlighted the critical role of SVM parameters (kernels, kernel parameters, feature selection) in classification accuracy.
The proposed Hybrid Intelligent System (HIS) demonstrated superior performance compared to the system with constant parameters.
Optimization through genetic algorithms significantly improved the recognition system's efficiency and accuracy.

Conclusions:

The optimized parameters are essential for achieving high SVM classification accuracy in ECG analysis.
The Hybrid Intelligent System (HIS) offers a more effective and efficient approach to ECG beat classification.
This study provides a foundation for developing advanced automated diagnostic tools for cardiac conditions.