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Related Concept Videos

Electrocardiogram01:29

Electrocardiogram

3.3K
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...
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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...
721
Pulse rhythm01:30

Pulse rhythm

946
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...
946
Dysrhythmias V: Evaluating Dysrhythmias01:30

Dysrhythmias V: Evaluating Dysrhythmias

127
Dysrhythmias, also known as arrhythmias, are disturbances in the heart's rhythm that range from benign to life-threatening. A thorough evaluation is crucial for appropriate management and involves a comprehensive medical history, physical examination, and various diagnostic tests.Medical HistorySymptoms: Collect detailed information on palpitations, dizziness, syncope, chest pain, and fatigue. Note their onset, frequency, and triggers.Previous Cardiac Issues: Document any history of heart...
127
Correlation between ECG and Cardiac Cycle01:25

Correlation between ECG and Cardiac Cycle

8.6K
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...
8.6K

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Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice
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[Artificial intelligence-based ECG analysis: current status and future perspectives-Part 2 : Recent studies and

Wilhelm Haverkamp1,2, Nils Strodthoff3, Carsten Israel4

  • 1Abteilung für Kardiologie und Metabolismus. Medizinische Klinik mit Schwerpunkt Kardiologie, Campus Virchow-Klinikum, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Deutschland. wilhelm.haverkamp@charite.de.

Herzschrittmachertherapie & Elektrophysiologie
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PubMed
Summary

Artificial intelligence (AI) enhances electrocardiogram (ECG) analysis by detecting diseases and predicting clinical events using deep learning. While promising, AI in ECG is still developing and requires further clinical validation.

Keywords:
Artificial neuronal networksDeep learningDigital healthElectrocardiographyMachine learning

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Area of Science:

  • Cardiology
  • Artificial Intelligence
  • Medical Technology

Background:

  • The application of artificial intelligence (AI) to electrocardiogram (ECG) analysis is rapidly expanding, particularly studies employing deep learning (DL) with artificial neural networks.
  • Recent advancements aim to surpass traditional ECG diagnostics by enabling the detection of cardiological and non-cardiological diseases and predicting clinical events.

Purpose of the Study:

  • To review recent studies on the practical applications of AI in ECG analysis.
  • To explore the potential of AI in extending ECG functionality beyond current diagnostic capabilities.

Main Methods:

  • Review of recent scientific literature on AI-based ECG analysis.
  • Focus on studies utilizing deep learning (DL) and artificial neural networks.
  • Analysis of AI's capability to identify subclinical patterns in large ECG datasets.

Main Results:

  • AI, particularly DL, can identify subtle patterns in extensive ECG data for algorithm development.
  • AI-assisted ECG analysis is emerging as a powerful screening tool, potentially exceeding cardiologist performance.
  • AI algorithms can predict clinical events like left ventricular dysfunction and atrial fibrillation.

Conclusions:

  • AI-based electrocardiography is in its early stages but shows remarkable progress and potential.
  • Most current studies are proof-of-concept, often using private data with unclear quality and limited clinical validation.
  • The 'black-box' nature of AI algorithms and the need for broader clinical validation remain significant challenges.