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Related Concept Videos

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....
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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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ECG Interpretation of Arrhythmias I: Sinus Arrhythmias01:16

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Arrhythmias are disturbances in the heart's rhythm that lead to abnormal heartbeats. These irregularities can originate from different parts of the heart and are classified based on their origin and nature.
Types of Arrhythmias
Sinus Node Arrhythmias
Sinus Bradycardia: Originating from the sinoatrial (SA) node, sinus bradycardia involves slower impulses, resulting in a heart rate of less than 60 beats per minute (bpm). Causes include sleep, vagal stimulation, beta-blockers, hypothyroidism,...
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Modified Boxplots00:57

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A standard box and whisker plot informs us about the spread of the data in a given sample. One can identify the minimum value, maximum value, first quartile value, second quartile or median value, and third quartile.
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ECG Interpretation of Arrhythmias II: Atrial, Junctional and Ventricular Arrhythmias01:25

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Arrhythmia is a condition characterized by an irregular heart rhythm, with ECG changes that differ based on its origin and nature. The types of arrhythmias discussed below include atrial, junctional, and ventricular arrhythmias.Atrial ArrhythmiasPremature Atrial Complexes (PACs): PACs are early atrial beats caused by stress, caffeine, alcohol, electrolyte imbalances, hypoxia, hyperthyroidism, or certain medications (e.g., bronchodilators and decongestants). The ECG shows early P waves with an...
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One of the common DNA damages is the chemical alteration of single bases by alkylation, oxidation, or deamination. The altered bases cause mispairing and strand breakage during replication. This type of damage causes minimal change to the DNA double helix structure and can be repaired by the base excision repair (BER) pathways. BER corrects damaged DNA sequences by removing the damaged base and restoring the original base sequence using the complementary strand as a template.
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Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities
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A new modified wavelet-based ECG denoising.

Zhaoyang Wang1, Junjiang Zhu1, Tianhong Yan1

  • 1School of Mechanical and Electrical Engineering, China Jiliang university , Hangzhou , China.

Computer Assisted Surgery (Abingdon, England)
|January 29, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces a novel wavelet design for electrocardiogram (ECG) signal denoising, effectively removing noise while preserving crucial signal features. The method enhances P and T waves and atrial fibrillation characteristics, improving signal quality for mobile medicine applications.

Keywords:
ECG signalsEMG interferenceatrial fibrillation signalsmodified waveletwavelet denoising

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Area of Science:

  • Biomedical Engineering
  • Signal Processing

Background:

  • Electrocardiogram (ECG) denoising is crucial for accurate diagnosis.
  • Wavelet denoising is common but can attenuate weak ECG features due to frequency overlap with electromyography (EMG) noise.

Purpose of the Study:

  • To develop a modified wavelet design for improved ECG signal denoising.
  • To enhance the retention and amplification of weak ECG signal characteristics.

Main Methods:

  • Optimized filter coefficients were derived by approximating an ideal filter's amplitude-frequency response.
  • A novel wavelet was constructed using these optimized coefficients.
  • The denoising algorithm was validated using clinical ECG data.

Main Results:

  • The proposed method effectively removed high-frequency noise from ECG signals.
  • Characteristic information of P waves, T waves, and atrial fibrillation signals was enhanced and retained.
  • The novel wavelet outperformed db4 and sym4 wavelets in improving signal-to-noise ratio and reducing mean square error.

Conclusions:

  • The modified wavelet design offers effective high-frequency noise removal while preserving and enhancing weak signal features.
  • This method provides theoretical guidance for ECG denoising in mobile medicine.
  • The approach is applicable to denoising other weak feature signals.