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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

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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...
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Dysrhythmias II: Classification of Tachyarrhythmias01:28

Dysrhythmias II: Classification of Tachyarrhythmias

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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...
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Dysrhythmias III: Characteristics of Dysrhythmias01:29

Dysrhythmias III: Characteristics of Dysrhythmias

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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...
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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.
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Dysrhythmias IV: Characteristics of Bradyarrhythmias01:18

Dysrhythmias IV: Characteristics of Bradyarrhythmias

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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...
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Disturbances in Heart Rhythm01:29

Disturbances in Heart Rhythm

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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.
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Updated: Oct 30, 2025

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A Detector for Premature Atrial and Ventricular Complexes.

Guadalupe García-Isla1, Luca Mainardi1, Valentina D A Corino1

  • 1Biosignals, Bioimaging and Bioinformatics Laboratory (B3Lab), Department of Electronics, Information and Bioengineering (DEIB), Politecnico di Milano, Milano, Italy.

Frontiers in Physiology
|July 5, 2021
PubMed
Summary

A new detector accurately identifies premature atrial complexes (PACs) and ventricular beats using heart rate variability and ECG features. This advancement improves detection sensitivity and specificity, crucial for studying PAC implications and monitoring arrhythmias.

Keywords:
ECG diagnosisatrial fibrillationbeat classifiermachine learningpremature atrial contractionspremature ventricular contractionsstrokesupraventricular ectopic beat

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Area of Science:

  • Cardiology
  • Biomedical Engineering
  • Signal Processing

Background:

  • The clinical significance of premature atrial complexes (PACs) regarding atrial fibrillation, stroke, and myocardial degradation remains unclear.
  • Existing PAC detection methods exhibit low sensitivity, hindering research and monitoring of PACs.
  • A robust PAC and ventricular beat detector is needed to advance the understanding and management of cardiac arrhythmias.

Purpose of the Study:

  • To develop and validate a novel algorithm for detecting premature atrial complexes (PACs) and ventricular beats.
  • To improve the sensitivity and specificity of cardiac arrhythmia detection compared to current state-of-the-art methods.
  • To provide a tool for better monitoring and study of PACs and their clinical implications.

Main Methods:

  • Utilized two PhysioNet open-source databases: the long-term ST database (LTSTDB) and the supraventricular arrhythmia database (SVDB).
  • Extracted features from electrocardiogram (ECG) signals, including heart rate variability (HRV) and morphological features from the 4th scale of the discrete wavelet transform (DWT).
  • Trained a random forest algorithm for binary and multi-label classification of normal (N), PAC (S), and ventricular (V) beats using a 10-fold cross-validation with patient-wise train-test division.

Main Results:

  • The algorithm achieved high median performance metrics: 99.29% sensitivity, 99.54% specificity, and 100% PPV for normal beats.
  • Demonstrated strong performance for PAC detection (95.83% sensitivity, 99.39% specificity, 35.68% PPV) and ventricular beat detection (100% sensitivity, 99.90% specificity, 79.63% PPV).
  • The proposed method significantly outperformed existing classifiers in PAC and ventricular beat detection sensitivity and PPV.

Conclusions:

  • The developed PAC and ventricular beat detector demonstrates superior performance compared to current state-of-the-art methods.
  • This advanced detection capability can facilitate further research into the relationship between PACs, atrial fibrillation, stroke, and myocardial health.
  • The validated algorithm offers a promising tool for clinical monitoring and management of cardiac arrhythmias.