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Related Concept Videos

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...
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...
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...
Correlation between ECG and Cardiac Cycle01:25

Correlation between ECG and Cardiac Cycle

The electrical signals recorded on an electrocardiogram (ECG) occur before the mechanical processes of contraction and relaxation during the cardiac cycle.
A cardiac action potential originates in the SA node and spreads throughout the atria and the AV node in approximately 0.03 seconds. This results in the P wave in an ECG and triggers atrial contraction. The action potential is then briefly slowed at the AV node, allowing the atria to contract and fill the ventricles with blood before...

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Related Experiment Video

Updated: May 14, 2026

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System
10:17

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System

Published on: April 11, 2025

A low-complexity ECG feature extraction algorithm for mobile healthcare applications.

Evangelos B Mazomenos, Dwaipayan Biswas, Amit Acharyya

    IEEE Journal of Biomedical and Health Informatics
    |January 31, 2013
    PubMed
    Summary
    This summary is machine-generated.

    This study presents a low-complexity algorithm for extracting electrocardiogram (ECG) fiducial points, crucial for remote cardiovascular monitoring on low-power devices. The method effectively balances computational efficiency with high performance, meeting essential requirements for wearable health technology.

    Related Experiment Videos

    Last Updated: May 14, 2026

    Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System
    10:17

    Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System

    Published on: April 11, 2025

    Area of Science:

    • Biomedical Engineering
    • Signal Processing
    • Cardiovascular Monitoring

    Background:

    • Remote cardiovascular monitoring requires efficient algorithms for low-power devices.
    • Extracting fiducial points from Electrocardiogram (ECG) signals is essential for accurate analysis.
    • Existing methods may face challenges with computational complexity and power consumption.

    Purpose of the Study:

    • To develop a low-complexity algorithm for ECG fiducial point extraction.
    • To optimize algorithms for computationally constrained devices in remote monitoring.
    • To achieve a balance between performance and computational cost.

    Main Methods:

    • Utilized the Discrete Wavelet Transform (DWT) with the Haar wavelet.
    • Employed modulus-maxima analysis on DWT coefficients for initial fiducial point approximation.
    • Incorporated a time-domain refinement stage based on ECG morphological properties.
    • Developed a hybrid time and frequency domain signal processing approach.

    Main Results:

    • The algorithm successfully extracted ECG fiducial points with high accuracy.
    • Performance was validated against manual annotations (QTDB) and state-of-the-art methods.
    • Evaluation on PTBDB signals showed compliance with all but one Common Standard for Electrocardiography (CSE) tolerance limit.
    • Complexity analysis demonstrated a favorable trade-off between computational operations and performance.

    Conclusions:

    • The proposed algorithm offers an ideal balance of low computational complexity and high performance for remote ECG monitoring.
    • This method is well-suited for deployment on low-power, resource-constrained devices.
    • The hybrid approach effectively addresses the challenges of ECG signal processing in remote healthcare applications.