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Electrocardiogram01:29

Electrocardiogram

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 the T...
Pulse rhythm01:30

Pulse rhythm

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 muscle...
ECG Interpretation of Rhythms01:24

ECG Interpretation of Rhythms

An electrocardiogram (ECG)graphically represents the heart's electrical activity on ECG paper or a monitor.
Components of the Electrocardiogram
The primary components of a normal ECG waveform in Normal sinus rhythm(NSR) include the P wave, PR interval, QRS complex, ST segment, T wave, and occasionally a U wave.
ECG waveforms are divided by vertical and horizontal lines at standard intervals.
The horizontal axis measures time and rate, and the vertical axis measures amplitude or voltage. When...
Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

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 to...
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...

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Related Experiment Video

Updated: May 14, 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

Sequential algorithm for the detection of the shockable rhythms in electrocardiogram.

Ji-Wook Jeong1, I B Lee, Yoonseon Song

  • 1Electronics & Telecommunications Research Institute, Daejeon, 305-701 South Korea. jwj@etri.re.kr

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|February 1, 2013
PubMed
Summary
This summary is machine-generated.

A new algorithm accurately detects ventricular fibrillation (VF) and ventricular tachycardia (VT) using 1-second ECG data, achieving 86.8% sensitivity and 99.4% specificity for shockable rhythms.

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A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis
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A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis

Published on: December 28, 2012

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Last Updated: May 14, 2026

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice
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A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis
18:11

A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis

Published on: December 28, 2012

Area of Science:

  • Biomedical Engineering
  • Cardiology
  • Signal Processing

Background:

  • Ventricular fibrillation (VF) and ventricular tachycardia (VT) are life-threatening arrhythmias.
  • Accurate and timely detection of these shockable rhythms is critical for patient survival.
  • Existing algorithms may have limitations in discriminating between shockable and non-shockable rhythms.

Purpose of the Study:

  • To develop and evaluate a sequential algorithm for detecting shockable ventricular arrhythmias (VF/VT > 180 bpm).
  • To assess the accuracy of a novel ECG analysis algorithm embedded in a portable bio-signal sensing module.
  • To discriminate between shockable and non-shockable cardiac rhythms.

Main Methods:

  • A sequential algorithm analyzes 1-second ECG episodes using data from the preceding 8 seconds.
  • The algorithm is designed to differentiate between shockable and non-shockable rhythms.
  • Performance was evaluated using 844,587 ECG episodes from established databases.

Main Results:

  • The algorithm achieved a sensitivity of 86.8% for detecting shockable rhythms.
  • A specificity of 99.4% was obtained, indicating high accuracy in identifying non-shockable rhythms.
  • Results were compared against previous findings in the field.

Conclusions:

  • The proposed VF/VT detection algorithm demonstrates high accuracy and potential for use in portable monitoring devices.
  • The algorithm effectively discriminates between critical shockable and non-shockable cardiac rhythms.
  • This method offers a promising advancement in real-time arrhythmia detection.