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Related Concept Videos

Electrocardiogram01:29

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...
Electrocardiogram Fundamentals01:28

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...
Correlation between ECG and Cardiac Cycle01:25

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 Rhythms01:24

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...

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Related Experiment Video

Updated: Jun 5, 2026

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice
06:07

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice

Published on: May 23, 2021

Wavelet Decomposition-Based Genomic Analysis of the Human Electrocardiogram.

Salma Zainana1, Larissa Lauer2,3, Tuomo Kiiskinen2

  • 1Institute for Computational & Mathematical Engineering, Stanford, CA, USA, 94305.

Medrxiv : the Preprint Server for Health Sciences
|June 4, 2026
PubMed
Summary

Analyzing electrocardiogram (ECG) frequency signals reveals new genetic links to heart conditions. High-frequency ECG components, often ignored, show strong genetic correlations with heart failure risk.

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Area of Science:

  • Cardiovascular Genetics
  • Biomedical Signal Processing
  • Genomics

Background:

  • Standard electrocardiogram (ECG) analysis reduces complex heart electrical activity to simple measurements, potentially losing valuable information.
  • The heritability and relevance of frequency-specific ECG signals to cardiovascular disease risk are not well understood.

Purpose of the Study:

  • To investigate the genetic basis of frequency-specific ECG signals.
  • To identify genetic loci associated with ECG waveform structure.
  • To explore the relationship between ECG spectral components and cardiovascular disease phenotypes.

Main Methods:

  • Decomposed resting 12-lead ECGs from 47,052 participants into 84 frequency-specific energy features using Daubechies-6 wavelet analysis.
  • Performed genome-wide association studies (GWAS) on each feature.
  • Utilized Bayesian fine-mapping to identify high-confidence causal variants.
  • Assessed SNP-based heritability and genetic correlations between ECG features and cardiovascular phenotypes from FinnGen.

Main Results:

  • Identified 67 independent genetic loci and 101 high-confidence causal variants associated with ECG frequency features.
  • Associated loci include genes critical for cardiac conduction and myocardial integrity (e.g., SCN5A, TTN, KCNQ1, DSP).
  • Found significant genetic correlations (up to 0.56) with heart failure, particularly driven by high-frequency ECG components (125-250 Hz).
  • SNP-based heritability estimates for ECG features ranged from 0.03 to 0.26.

Conclusions:

  • The electrocardiogram can be viewed as a multi-frequency genetic phenotype.
  • ECG frequency analysis expands the discovery of cardiac genetic loci.
  • High-frequency cardiac electrical activity represents an underexplored area in cardiovascular disease risk.