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Related Concept Videos

Electrocardiogram01:29

Electrocardiogram

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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...
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Correlation between ECG and Cardiac Cycle01:25

Correlation between ECG and Cardiac Cycle

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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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Pulse rhythm01:30

Pulse rhythm

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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...
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ECG Interpretation of Rhythms01:24

ECG Interpretation of Rhythms

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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....
12.8K
Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

1.4K
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...
1.4K
Holter Monitor: 24-Hour Monitoring01:23

Holter Monitor: 24-Hour Monitoring

2.1K
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: Jan 18, 2026

Calculating Heart Rate Variability from ECG Data from Youth with Cerebral Palsy During Active Video Game Sessions
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Continuous Estimation of Heart Rate Variability from Electrocardiogram and Photoplethysmogram Signals with

Maksim O Zhuravlev1, Anastasiya E Runnova1,2, Sergei A Mironov1

  • 1Coordinating Center for Fundamental Research, National Medical Research Center for Therapy and Preventive Medicine, 101990 Moscow, Russia.

Sensors (Basel, Switzerland)
|September 13, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a new heart rate (HR) detection method using continuous wavelet transform, applicable to ECG and PPG signals. The novel approach shows high accuracy and robustness against signal noise, offering improved HRV analysis.

Keywords:
electrocardiogramheart rate variabilitynumerical processingoscillatory wavelet patternsphotoplethysmogram

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Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Cardiovascular Physiology

Background:

  • Accurate heart rate (HR) monitoring is crucial for diagnosing cardiac conditions and assessing overall health.
  • Traditional HR detection methods, such as R-peak analysis, can be sensitive to signal noise and distortion.
  • Time-frequency analysis offers a promising avenue for robust signal processing in biomedical applications.

Purpose of the Study:

  • To develop and validate a novel heart rate detection method utilizing continuous wavelet transform (CWT) for time-frequency analysis.
  • To assess the applicability of the CWT-based method for both electrocardiogram (ECG) and photoplethysmogram (PPG) signals.
  • To compare the performance of the proposed HR detection technique against traditional R-peak analysis.

Main Methods:

  • The proposed method analyzes oscillatory patterns derived from CWT for HR detection.
  • Experiments were conducted on ECG (lead V1) and PPG signals from 40 healthy volunteers over 10-minute recordings.
  • Performance was evaluated against a conventional HR detection method based on R-peak shape analysis.

Main Results:

  • The CWT-based HR detection method demonstrated an acceptable degree of agreement with the traditional method, with discrepancies not exceeding 3.41%.
  • The proposed technique proved robust against signal distortion and noise, requiring no additional filtering.
  • Successful HR detection was achieved even with differential PPG signals and during patient ambulation (walking).

Conclusions:

  • The novel CWT-based approach provides a reliable method for heart rate detection from both ECG and PPG signals.
  • This method offers enhanced equidistant sampling frequency for HR data and expands insights into heart rate variability (HRV) frequency composition.
  • The technique's resilience to signal artifacts makes it suitable for real-world, potentially noisy, physiological monitoring scenarios.