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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 minute.

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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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: Jun 14, 2026

A Model of Long-Term Ventricular Fibrillation in Isolated Rat Hearts

A Model of Long-Term Ventricular Fibrillation in Isolated Rat Hearts

Published on: February 17, 2023

Phase statistics approach to human ventricular fibrillation.

Ming-Chya Wu¹, Eiichi Watanabe, Zbigniew R Struzik

¹Research Center for Adaptive Data Analysis, National Central University, Chungli 32001, Taiwan. mcwu@ncu.edu.tw

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics

|April 7, 2010

Summary

Ventricular fibrillation (VF) is a dangerous heart rhythm. Analyzing ECG phase statistics reveals distinct patterns, with convex phase distributions indicating zero survival probability, suggesting VF episodes are never self-terminating.

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Last Updated: Jun 14, 2026

A Model of Long-Term Ventricular Fibrillation in Isolated Rat Hearts

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

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Ablation of Ischemic Ventricular Tachycardia Using a Multipolar Catheter and 3-dimensional Mapping System for High-density Electro-anatomical Reconstruction

Ablation of Ischemic Ventricular Tachycardia Using a Multipolar Catheter and 3-dimensional Mapping System for High-density Electro-anatomical Reconstruction

Published on: January 31, 2019

Area of Science:

Cardiology
Physiology
Data Science

Background:

Ventricular fibrillation (VF) is a life-threatening cardiac arrhythmia causing sudden cardiac death (SCD).
While electrical defibrillation is standard, some VF episodes spontaneously terminate, a mechanism not fully understood.
Understanding spontaneous defibrillation could lead to novel therapeutic strategies.

Purpose of the Study:

To investigate the timing characteristics of transient features in ventricular tachyarrhythmia (VF) electrocardiogram (ECG) using phase statistics.
To identify distinct patterns in phase distributions that correlate with VF self-termination and patient survival.

Main Methods:

Application of the phase statistics approach, a method developed for financial and physiological time series analysis.
Analysis of human ECG data during ventricular tachyarrhythmia, focusing on phase distribution patterns.
Categorization of phase distributions into uniform (UF), concave (CC), and convex (CV) types.

Main Results:

Three distinct types of phase probability density function (PDF) were identified: UF, CC, and CV.
VF patients with UF or CC PDF types showed similar probabilities of survival and nonsurvival.
VF patients with CV type PDF exhibited zero probability of survival, indicating non-self-terminating episodes.

Conclusions:

Detailed phase statistics of human ECG data offer insights into the mechanisms of spontaneous defibrillation in VF.
The CV phase distribution pattern is a strong indicator of non-self-terminating VF, associated with zero survival.
This analysis may pave the way for improved prediction and treatment of fatal ventricular fibrillation.