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Related Concept Videos

Electrocardiogram01:29

Electrocardiogram

5.3K
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...
5.3K
Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

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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...
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Instrumentation Amplifier01:25

Instrumentation Amplifier

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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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Pulse rhythm01:30

Pulse rhythm

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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: Jan 9, 2026

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System
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Artificial intelligence-enabled electrocardiography from scientific research to clinical application.

Chin-Sheng Lin1,2,3, Wei-Ting Liu1, Yuan-Hao Chen4

  • 1Division of Cardiology, Department of Internal Medicine, Tri-Service General Hospital, National Defense Medical University, Taipei, Taiwan, ROC.

EMBO Molecular Medicine
|December 1, 2025
PubMed
Summary

Artificial intelligence (AI) is transforming electrocardiography (ECG) diagnostics by analyzing complex data to detect cardiovascular conditions earlier. AI-ECG aids in risk stratification and community screening, improving patient outcomes.

Keywords:
Artificial IntelligenceDigital BiomarkerElectrocardiographyOpportunistic ScreeningParadigm Shift

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Area of Science:

  • Cardiology
  • Medical Diagnostics
  • Artificial Intelligence

Background:

  • Traditional electrocardiography (ECG) interpretation relies on established criteria.
  • Human interpretation has limitations in detecting subtle patterns.
  • Advancements in AI offer new diagnostic capabilities.

Purpose of the Study:

  • To review the impact of AI on ECG analysis in cardiovascular diagnostics.
  • To highlight how AI overcomes limitations of human interpretation.
  • To discuss AI applications in risk stratification and screening.

Main Methods:

  • Review of recent advancements in AI, particularly deep learning algorithms.
  • Analysis of AI's capacity to process complex, high-dimensional ECG data.
  • Examination of findings from randomized controlled trials (RCTs) on AI-ECG integration.

Main Results:

  • AI models identify patterns missed by conventional methods, such as asymptomatic low ejection fraction and paroxysmal atrial fibrillation.
  • AI integration in clinical workflows reduces intervention times.
  • AI effectively identifies patients at elevated risk of adverse cardiovascular outcomes.

Conclusions:

  • AI significantly enhances ECG's diagnostic utility for cardiovascular diseases.
  • AI-ECG facilitates earlier clinical intervention and improved risk stratification.
  • Future work includes integrating diverse data sources and enhancing AI model interpretability.