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Related Concept Videos

ECG Interpretation of Arrhythmias II: Atrial, Junctional and Ventricular Arrhythmias01:25

ECG Interpretation of Arrhythmias II: Atrial, Junctional and Ventricular Arrhythmias

Arrhythmia is a condition characterized by an irregular heart rhythm, with ECG changes that differ based on its origin and nature. The types of arrhythmias discussed below include atrial, junctional, and ventricular arrhythmias.Atrial ArrhythmiasPremature Atrial Complexes (PACs): PACs are early atrial beats caused by stress, caffeine, alcohol, electrolyte imbalances, hypoxia, hyperthyroidism, or certain medications (e.g., bronchodilators and decongestants). The ECG shows early P waves with an...
Dysrhythmias III: Characteristics of Dysrhythmias01:29

Dysrhythmias III: Characteristics of Dysrhythmias

Dysrhythmias, also known as arrhythmias, are irregular heart rhythms that result from abnormal electrical activity in the heart, affecting its ability to circulate blood efficiently. Tachyarrhythmias, a subset of dysrhythmias, are characterized by abnormally fast heart rates exceeding 100 beats per minute. Here are some types of tachyarrhythmias with their distinct ECG features:Sinus Tachycardia:Sinus tachycardia presents a regular heart rhythm with an increased rate of 101-180 beats per minute.
Disturbances in Heart Rhythm01:29

Disturbances in Heart Rhythm

Arrhythmia or dysrhythmia refers to an abnormal heart rhythm caused by a defect in the heart's conduction system. It can cause the heart to beat irregularly, too quickly, or too slowly, leading to symptoms like chest pain, shortness of breath, and fainting. Factors such as stress, caffeine, alcohol, nicotine, cocaine, certain drugs, congenital defects, diseases, and electrolyte abnormalities can trigger arrhythmias.
Arrhythmias are categorized by their speed, rhythm, and origin. A slow heart...
Dysrhythmias II: Classification of Tachyarrhythmias01:28

Dysrhythmias II: Classification of Tachyarrhythmias

Tachyarrhythmias are a type of dysrhythmia where the heart rate exceeds 100 beats per minute. Here are some common types of tachyarrhythmias:Sinus TachycardiaSinus tachycardia originates from increased impulses from the sinus node, leading to an elevated heart rate. It is often triggered by stress, fever, or exercise.Patients may experience palpitations, a sensation of a racing heart, dizziness, and chest discomfort.Causes and Risk Factors: Common causes include physical exertion, emotional...
Dysrhythmias IV: Characteristics of Bradyarrhythmias01:18

Dysrhythmias IV: Characteristics of Bradyarrhythmias

Bradyarrhythmias are cardiac rhythm disorders characterized by a slower-than-normal heart rate, typically defined as fewer than 60 beats per minute. Some of which are discussed here:Sinus BradycardiaSinus bradycardia presents a heart rate lower than 60 beats per minute, with a regular rhythm originating from the SA node. The ECG typically shows normal P waves preceding each QRS complex, a normal PR interval (0.12 to 0.20 seconds), and a normal QRS duration (0.06 to 0.10 seconds).First-Degree AV...
Dysrhythmias V: Evaluating Dysrhythmias01:30

Dysrhythmias V: Evaluating Dysrhythmias

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...

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Related Experiment Video

Updated: May 25, 2026

High-Resolution Endocardial and Epicardial Optical Mapping in a Sheep Model of Stretch-Induced Atrial Fibrillation
09:17

High-Resolution Endocardial and Epicardial Optical Mapping in a Sheep Model of Stretch-Induced Atrial Fibrillation

Published on: July 29, 2011

Atrial fibrillation source identification.

Raja Sarath Chandra Prasad Vaizurs1, Ravi Sankar, Fabio Leonelli

  • 1Department of Electrical Engineering, College of Engineering, University of South Florida, USA.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|January 19, 2012
PubMed
Summary
This summary is machine-generated.

Identifying atrial fibrillation triggers is key for permanent treatment. This study introduces a new algorithm analyzing pulmonary vein signals to precisely locate these arrhythmia sources.

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Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation
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Robotic Ablation of Atrial Fibrillation
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Robotic Ablation of Atrial Fibrillation

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Last Updated: May 25, 2026

High-Resolution Endocardial and Epicardial Optical Mapping in a Sheep Model of Stretch-Induced Atrial Fibrillation
09:17

High-Resolution Endocardial and Epicardial Optical Mapping in a Sheep Model of Stretch-Induced Atrial Fibrillation

Published on: July 29, 2011

Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation
08:10

Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation

Published on: July 20, 2022

Robotic Ablation of Atrial Fibrillation
11:21

Robotic Ablation of Atrial Fibrillation

Published on: May 29, 2015

Area of Science:

  • Cardiology
  • Biomedical Engineering
  • Signal Processing

Background:

  • Atrial fibrillation (AF) is a prevalent arrhythmia linked to significant morbidity and mortality.
  • Current treatments, including medications and invasive procedures, often provide only temporary relief.
  • Targeting the triggers of AF is crucial for achieving a permanent cure.

Purpose of the Study:

  • To develop and validate a novel algorithm for identifying the specific sources of atrial fibrillation.
  • To classify electrophysiological signals from the pulmonary veins to pinpoint AF origins.

Main Methods:

  • Analysis of complex endocardial recordings from the left atrium.
  • Development of a classification algorithm focused on signals from the four pulmonary veins.
  • Utilizing signal processing techniques to differentiate between normal and arrhythmogenic signals.

Main Results:

  • The proposed algorithm successfully identifies signals originating from the pulmonary veins.
  • Demonstrated the capability to classify signals indicative of atrial fibrillation triggers.
  • Potential for precise localization of AF sources within the pulmonary veins.

Conclusions:

  • This novel algorithm offers a promising approach for accurately detecting atrial fibrillation triggers.
  • Precise identification of triggers, particularly within the pulmonary veins, could lead to more effective and permanent AF treatment strategies.
  • The findings support the targeted destruction of identified triggers as a viable curative method for AF.