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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...

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...

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....

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...

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Related Experiment Video

Updated: Oct 10, 2025

Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis

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Deep Learning-Based Data-Point Precise R-Peak Detection in Single-Lead Electrocardiograms.

M D Oudkerk Pool, B D de Vos, M M Winter

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

|December 11, 2021

Summary

A new deep learning method precisely detects R-peaks in electrocardiograms (ECG), improving cardiac arrhythmia screening. This advancement in R-peak detection is crucial for accurate diagnosis using wearable devices.

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Area of Science:

Biomedical Engineering
Artificial Intelligence in Medicine
Cardiology

Background:

Low-cost wearable devices increasingly record single-lead electrocardiograms (ECG).
These ECGs are primarily used for screening cardiac arrhythmias like atrial fibrillation.
Accurate R-peak detection is essential for automated arrhythmia diagnosis, but current methods lack precision.

Purpose of the Study:

To develop a data-point precise R-peak detection method.
To enhance automated cardiac arrhythmia detection using wearable ECGs.

Main Methods:

A fully convolutional dilated neural network was proposed for R-peak detection.
The network was trained and validated using manually annotated R-peaks from heterogeneous ECGs.
A dataset of 700 ECGs from the PhysioNet/CinC challenge 2017 was utilized.

Main Results:

The proposed network achieved high performance on the test set.
Precision: 0.910
Recall: 0.926
F1-score: 0.918

Conclusions:

The developed method enables data-point precise R-peak detection.
This offers a significant advancement for automated cardiac arrhythmia detection and characterization.
It provides a foundation for improved diagnostic capabilities in wearable ECG technology.