Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Electrocardiogram01:29

Electrocardiogram

7.5K
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...
7.5K
ECG Interpretation of Rhythms01:24

ECG Interpretation of Rhythms

17.8K
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....
17.8K
Correlation between ECG and Cardiac Cycle01:25

Correlation between ECG and Cardiac Cycle

14.5K
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...
14.5K
Instrumentation Amplifier01:25

Instrumentation Amplifier

1.2K
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...
1.2K
Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

1.9K
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...
1.9K
Pulse rhythm01:30

Pulse rhythm

1.6K
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...
1.6K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Prediction of Nocturnal Hypoglycemia Following Exercise in Type 1 Diabetes Using Temporally Structured CGM-Derived Digital Biomarkers.

Sensors (Basel, Switzerland)·2026
Same author

Role of Electroencephalography in the Assessment of Cortical Responses Elicited by Music Therapy in Burn Patients Undergoing Intensive Care.

Sensors (Basel, Switzerland)·2026
Same author

Clinically interpretable nomogram combining body composition and clinicopathological features for one year survival prediction in advanced solid tumors.

Scientific reports·2026
Same author

Assessment of the Psycho-Emotional State Induced by Open-Skill Sport Activity: An Electroencephalography-Based Study.

Sensors (Basel, Switzerland)·2026
Same author

Heart Sound Classification for Early Detection of Cardiovascular Diseases Using XGBoost and Engineered Acoustic Features.

Sensors (Basel, Switzerland)·2026
Same author

Acoustic analysis of bottlenose dolphin vocalizations for behavioral classification in controlled settings.

PloS one·2025
Same journal

Development and experimental characterization of a cadaveric stance simulator for residual limb biomechanics.

Medical engineering & physics·2026
Same journal

Rapid personalized computational modeling of the wrist.

Medical engineering & physics·2026
Same journal

SHAP-enabled explainable AI framework for clinical interpretation of valvular heart diseases via digital acoustic features.

Medical engineering & physics·2026
Same journal

Three-dimensional motion analysis of a total wrist prosthesis during the dart-throwing motion: a cadaveric study.

Medical engineering & physics·2026
Same journal

Patient-specific left ventricular hypertrophy under severe hypertension: mechanistic insights from Hill-type computational simulations.

Medical engineering & physics·2026
Same journal

Enabling laboratory-based personalization of musculoskeletal spine models: a standardized rail-guided ultrasound method.

Medical engineering & physics·2026
See all related articles

Related Experiment Video

Updated: Mar 22, 2026

Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis
08:22

Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis

Published on: April 26, 2024

3.4K

Segmented beat modulation method for electrocardiogram estimation from noisy recordings.

Angela Agostinelli1, Agnese Sbrollini1, Corrado Giuliani1

  • 1Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy.

Medical Engineering & Physics
|April 28, 2016
PubMed
Summary
This summary is machine-generated.

A new Segmented-Beat Modulation Method (SBMM) effectively filters noisy electrocardiograms (ECGs), preserving vital physiological variability. This advanced ECG processing technique offers superior noise robustness compared to standard methods.

Keywords:
Digital ECG processingECG filtering procedureTemplate-based ECG estimation

More Related Videos

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

4.5K
Real-Time Electrocardiogram Monitoring During Treadmill Training in Mice
04:45

Real-Time Electrocardiogram Monitoring During Treadmill Training in Mice

Published on: May 5, 2022

3.1K

Related Experiment Videos

Last Updated: Mar 22, 2026

Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis
08:22

Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis

Published on: April 26, 2024

3.4K
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

4.5K
Real-Time Electrocardiogram Monitoring During Treadmill Training in Mice
04:45

Real-Time Electrocardiogram Monitoring During Treadmill Training in Mice

Published on: May 5, 2022

3.1K

Area of Science:

  • Biomedical Engineering
  • Signal Processing
  • Cardiology

Background:

  • Noisy electrocardiogram (ECG) recordings can compromise clinical utility.
  • Existing template-based ECG estimation methods often fail to reproduce physiological variability.
  • Physiological ECG variability is crucial for patient health assessment.

Purpose of the Study:

  • To introduce the Segmented-Beat Modulation Method (SBMM) for ECG noise reduction.
  • To evaluate SBMM's ability to reproduce ECG variability.
  • To compare SBMM's robustness against noise with a Standard Template Method (STM).

Main Methods:

  • Developed SBMM, a novel template-based filtering procedure.
  • SBMM segments ECG into QRS and TUP components.
  • Employs modulation/demodulation of segments to adapt beat morphology and duration.

Main Results:

  • SBMM significantly reduces ECG estimation errors compared to STM across various noise levels.
  • SBMM shows lower errors for QRS segments (176-232µV) and TUP segments (79-499µV) versus STM (215-496µV and 93-1056µV, respectively).
  • SBMM successfully reproduces ECG variability while maintaining noise robustness.

Conclusions:

  • SBMM is a robust and effective method for processing noisy ECG recordings.
  • The SBMM technique preserves essential ECG variability, enhancing diagnostic value.
  • SBMM offers improved performance over standard template methods in challenging noise conditions.