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Related Concept Videos

Electrocardiogram01:29

Electrocardiogram

5.0K
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...
5.0K
Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

1.2K
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...
1.2K
ECG Interpretation of Rhythms01:24

ECG Interpretation of Rhythms

10.9K
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....
10.9K
Pulse rhythm01:30

Pulse rhythm

1.2K
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...
1.2K
Correlation between ECG and Cardiac Cycle01:25

Correlation between ECG and Cardiac Cycle

11.2K
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...
11.2K
Instrumentation Amplifier01:25

Instrumentation Amplifier

929
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...
929

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Related Experiment Video

Updated: Dec 18, 2025

A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis
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A Research Method For Detecting Transient Myocardial Ischemia In Patients With Suspected Acute Coronary Syndrome Using Continuous ST-segment Analysis

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Detection and analysis: driver state with electrocardiogram (ECG).

Suganiya Murugan1, Jerritta Selvaraj1, Arun Sahayadhas2

  • 1Artificial Intelligence Research Lab, Vels Institute of Science, Technology and Advanced Studies, Chennai, India.

Physical and Engineering Sciences in Medicine
|June 12, 2020
PubMed
Summary
This summary is machine-generated.

Monitoring driver

Keywords:
Cognitive inattentionDrowsinessElectrocardiogramFatigueVisual inattention

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Area of Science:

  • Physiological signal analysis
  • Road safety research
  • Machine learning applications

Background:

  • Driver drowsiness, fatigue, and inattention are primary causes of road accidents.
  • Physiological signals offer reliable insights into a driver's internal state.
  • Electrocardiogram (ECG) signals can track heart rate and variability.

Purpose of the Study:

  • To detect and analyze driver states using electrocardiogram (ECG) data.
  • To evaluate the effectiveness of different machine learning classifiers for driver state detection.
  • To assess the accuracy of classifying various driver states.

Main Methods:

  • ECG signals were filtered, and 13 statistically significant features were extracted.
  • Features were trained using Support Vector Machine (SVM), K-nearest neighbour (KNN), and Ensemble classifiers.
  • Classification accuracy was evaluated for two-class and five-class scenarios.

Main Results:

  • Two-class detection achieved high accuracies: 100% for normal-drowsy, 93.1% for normal-visual inattention, 96.6% for normal-fatigue, and 96.6% for normal-cognitive inattention.
  • The Ensemble classifier achieved 58.3% accuracy for five-class detection.
  • Two-class detection demonstrated superior accuracy compared to multi-class detection.

Conclusions:

  • ECG-based analysis is a promising method for monitoring driver states.
  • Two-class classification of driver states yields highly accurate results.
  • Further development of algorithms is needed to improve multi-class detection accuracy.