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Related Concept Videos

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...
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...
Instrumentation Amplifier01:25

Instrumentation Amplifier

An electrocardiography (ECG) machine is an essential piece of medical equipment used to monitor the electrical activity of the heart. It operates by detecting small electrical changes on the skin that result from the depolarization of the heart muscle during each heartbeat. However, these signals are in the microvolt range and can be easily overwhelmed by noise or interference.
To overcome this challenge, an ECG machine utilizes an instrumentation amplifier. This specialized amplifier is...
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...
Bode Plots Construction01:24

Bode Plots Construction

The Bode plot is an essential tool in control system analysis, mapping the frequency response of a system through a magnitude plot and a phase plot, both against a logarithmic frequency axis. To construct a Bode plot, consider the transfer function H(ω):
Holter Monitor: 24-Hour Monitoring01:23

Holter Monitor: 24-Hour Monitoring

Holter monitoring is a continuous electrocardiography (ECG) recording that tracks the heart's electrical activity over an extended period, generally 24 to 48 hours. This noninvasive diagnostic tool detects irregular heart rhythms that may not be captured during a standard ECG performed in a clinical setting.DeviceThe Holter monitor is a portable, small device connected to several electrodes on the patient's chest. These electrodes detect the heart's electrical signals and transmit them to the...

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Related Experiment Video

Updated: May 19, 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

ECG feature extraction using differentiation, Hilbert transform, variable threshold and slope reversal approach.

S K Mukhopadhyay1, M Mitra, S Mitra

  • 1Department of Applied Physics, University of Calcutta, Kolkata, India. sonartoritag@yahoo.co.in

Journal of Medical Engineering & Technology
|September 6, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces an accurate electrocardiogram (ECG) feature extraction algorithm. The method reliably detects key ECG components like R-peaks, improving diagnostic accuracy.

Related Experiment Videos

Last Updated: May 19, 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
  • Cardiology

Background:

  • Accurate electrocardiogram (ECG) analysis is crucial for diagnosing cardiac conditions.
  • Existing ECG feature extraction methods can be sensitive to noise and baseline wander.
  • Robust detection of ECG waves (P, QRS, T) and fiducial points is essential for quantitative analysis.

Purpose of the Study:

  • To develop and validate an accurate and reliable algorithm for ECG feature extraction.
  • To enhance the detection of R-peaks, QRS complexes, and other ECG waveform components.
  • To assess the performance of the proposed algorithm in terms of sensitivity, positive predictivity, and accuracy.

Main Methods:

  • ECG signal preprocessing including denoising.
  • Computation of the first derivative and Hilbert transform for feature identification.
  • Detection of R-peaks based on maximum amplitude and slope reversals.
  • Identification of Q, S peaks, QRS onset-offset, P, and T waves.
  • ECG baseline wander correction post-feature detection.

Main Results:

  • The algorithm demonstrates high sensitivity, positive predictivity, and accuracy in R-peak detection.
  • Successful detection of QRS onset-offset points, P waves, and T waves.
  • Accurate measurement of wave and segment durations and peak heights.
  • Calculation of measurement errors for extracted ECG features.

Conclusions:

  • The developed algorithm provides a robust and accurate method for ECG feature extraction.
  • The algorithm effectively addresses challenges like noise and baseline modulation.
  • This approach can significantly aid in the quantitative analysis of ECG signals for clinical applications.