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Related Concept Videos

Electrocardiogram01:29

Electrocardiogram

5.3K
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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Holter Monitor: 24-Hour Monitoring01:23

Holter Monitor: 24-Hour Monitoring

2.0K
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...
2.0K
ECG Interpretation of Rhythms01:24

ECG Interpretation of Rhythms

12.4K
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....
12.4K
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
Correlation between ECG and Cardiac Cycle01:25

Correlation between ECG and Cardiac Cycle

11.7K
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...
11.7K
Pulse rhythm01:30

Pulse rhythm

1.3K
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...
1.3K

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Related Experiment Video

Updated: Jan 14, 2026

Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function
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Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function

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Age estimation via electrocardiogram from smartwatches.

Azfar Adib1, Wei-Ping Zhu1, M Omair Ahmad1

  • 1Department of Electrical and Computer Engineering, Concordia University, Montreal, QC Canada.

Npj Biomedical Innovations
|October 27, 2025
PubMed
Summary
This summary is machine-generated.

Smartwatch electrocardiogram (ECG) signals can estimate age accurately, outperforming clinical ECG methods. This technology offers a privacy-preserving solution for age verification, especially for online child protection.

Keywords:
CardiologyComputational biology and bioinformatics

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Area of Science:

  • Biomedical Engineering
  • Digital Health
  • Machine Learning

Background:

  • Accurate age estimation is crucial for age-restricted services and online child safety.
  • Traditional age verification methods (ID checks, facial recognition) present privacy and reliability issues.
  • Electrocardiogram (ECG) signals exhibit age-dependent characteristics, offering a potential biometric alternative.

Purpose of the Study:

  • To investigate the feasibility of using smartwatch-derived ECG signals for age estimation.
  • To develop and evaluate machine learning models for age prediction using wearable ECG data.
  • To compare the performance of smartwatch ECG-based age estimation against traditional and clinical ECG methods.

Main Methods:

  • Collected a novel dataset of smartwatch ECGs from 220 individuals spanning a wide age range.
  • Extracted and analyzed various ECG features relevant to age-related physiological changes.
  • Trained and tested multiple machine learning models to predict age and perform binary age classification.

Main Results:

  • Achieved a mean absolute error (MAE) of 2.93 years in age estimation, surpassing clinical ECG-based studies.
  • Demonstrated peak accuracy during adolescence, correlating with significant ECG developmental changes.
  • Attained high accuracy (93-96%) for binary age classification within the 13-21 year range.

Conclusions:

  • Smartwatch ECG signals provide a viable and accurate method for non-invasive age estimation.
  • This approach offers a privacy-conscious alternative to conventional age verification techniques.
  • Wearable ECG technology holds significant potential for applications requiring reliable age assessment, particularly in digital environments.