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Related Concept Videos

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...
Mechanism of Cardiac Arrhythmias01:28

Mechanism of Cardiac Arrhythmias

Arrhythmias are irregular heart rhythms occurring when the heart's electrical impulses become abnormal. These disturbances can lead to various symptoms, depending on their severity and the underlying cause. Some common factors contributing to arrhythmias include hypoxia, ischemia, electrolyte imbalances, excessive catecholamine exposure, drug toxicity, and muscle overstretching. Arrhythmias can be classified into two main types based on the rate and site of origin of abnormal heart rhythms.
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...
Cardiopulmonary Resuscitation III: AED Use01:23

Cardiopulmonary Resuscitation III: AED Use

Introduction to AEDAn Automated External Defibrillator (AED) is a portable medical device that analyzes the heart's rhythm and, if necessary, delivers an electrical shock to help the heart re-establish an effective rhythm during sudden cardiac arrest (SCA). SCA occurs when the heart suddenly and unexpectedly stops beating, leading to a loss of blood flow to the brain and other vital organs. In such emergencies, time is of the essence, and using an AED, combined with Cardiopulmonary...
Dysrhythmias VI: Management of Dysrhythmias01:25

Dysrhythmias VI: Management of Dysrhythmias

Dysrhythmia management involves a multifaceted approach, incorporating pharmacological treatments, medical procedures, surgical interventions, lifestyle modifications, and patient education.Pharmacological ManagementAntiarrhythmic Drugs:Class I (Sodium Channel Blockers): This class includes quinidine and procainamide, which reduce the speed of impulse conduction in the heart, stabilize the cardiac membrane, and control arrhythmias. Quinidine and procainamide are Class IA agents that prolong the...

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Related Experiment Video

Updated: Jun 5, 2026

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice
06:07

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice

Published on: May 23, 2021

A multi-stage automatic arrhythmia recognition and classification system.

Yakup Kutlu1, Damla Kuntalp

  • 1Dokuz Eylül University, İzmir, Turkey. yakup.kutlu@deu.edu.tr

Computers in Biology and Medicine
|December 25, 2010
PubMed
Summary
This summary is machine-generated.

This study presents an automatic heartbeat recognition system using diverse features and a three-stage k-nearest neighbor classification. The system accurately classifies 16 heartbeat types from ECG data, achieving high sensitivity, selectivity, and specificity.

Related Experiment Videos

Last Updated: Jun 5, 2026

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice
06:07

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice

Published on: May 23, 2021

Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Machine Learning

Background:

  • Accurate electrocardiogram (ECG) analysis is crucial for diagnosing cardiac conditions.
  • Automated heartbeat classification systems aim to improve diagnostic efficiency and accuracy.

Purpose of the Study:

  • To develop and evaluate an automatic heartbeat recognition system using a combination of diverse features.
  • To classify heartbeats into 16 distinct types with high accuracy.

Main Methods:

  • A three-stage classification approach employing the k-nearest neighbor algorithm.
  • Extraction of diverse features including statistical, morphological, Fourier, and wavelet coefficients.
  • Utilized the MIT-BIH arrhythmia database for training and testing.

Main Results:

  • The system achieved an average sensitivity of 85.59%, selectivity of 95.46%, and specificity of 99.56%.
  • Successfully classified 16 different types of heartbeats.
  • Demonstrated the effectiveness of combining diverse features for robust classification.

Conclusions:

  • The proposed automatic heartbeat classification system demonstrates high performance in recognizing various arrhythmia types.
  • The multi-stage feature selection and k-nearest neighbor approach provide a reliable method for ECG beat classification.