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Electrocardiogram

Electrocardiogram

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.
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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.
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Updated: Jun 6, 2025

Measuring Cardiac Autonomic Nervous System ANS Activity in Children

Measuring Cardiac Autonomic Nervous System ANS Activity in Children

Published on: April 29, 2013

Tracking autonomic nervous system activity using surface ECG: Personalized, multiparametric evaluation.

Vladimir Shusterman¹, Cees A Swenne², Stacy Hoffman³

¹Division of Cardiovascular Medicine, The University of Iowa, Iowa City, IA, United States of America; PinMed, Inc., Pittsburgh, PA, United States of America.

Journal of Electrocardiology

|November 30, 2024

Summary

This summary is machine-generated.

Accurately tracking cardiac autonomic nervous system activity (ANSA) outside the lab is challenging due to uncontrolled factors. Multiparametric monitoring and machine learning are key to reliable, personalized ANSA evaluation in real-world settings.

Keywords:

Autonomic nervous system Cardiac repolarization variability Cardiac rhythm monitoring Heart rate variability Wearable cardiovascular devices

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Measuring Cardiac Autonomic Nervous System ANS Activity in Children

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Published on: April 29, 2013

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Published on: July 19, 2011

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Published on: April 26, 2024

Area of Science:

Cardiovascular Physiology
Autonomic Nervous System Research
Biomedical Signal Processing

Background:

Cardiac autonomic nervous system activity (ANSA) is crucial for cardiovascular health.
Surface-ECG parameters like heart rate (HR) and heart-rate variability (HRV) offer insights into ANSA.
Current methods face limitations in uncontrolled ambulatory settings.

Purpose of the Study:

To review challenges and solutions for noninvasive, continuous ANSA tracking.
To highlight the limitations of single-parameter evaluations in ambulatory settings.
To propose strategies for improving the accuracy of ANSA assessment.

Main Methods:

Review of ECG-accessible parameters: HR, HRV, and cardiac repolarization.
Analysis of uncontrolled ambulatory factors affecting ANSA evaluation (e.g., blood pressure, physical activity, respiration).
Discussion of multisensor, multiparametric monitoring and data fusion techniques.

Main Results:

Single-parameter ANSA evaluation in ambulatory settings can be inaccurate.
Uncontrolled factors significantly confound ANSA assessment.
Multisensor, multiparametric approaches are necessary for improved accuracy.

Conclusions:

Accurate ambulatory ANSA evaluation requires tracking multiple physiological processes.
Controlling variables like respiration and employing data fusion are essential.
Machine learning analytics are vital for developing personalized ANSA evaluations.