Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Correlation between ECG and Cardiac Cycle01:25

Correlation between ECG and Cardiac Cycle

3.3K
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...
3.3K
Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

482
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...
482
Instrumentation Amplifier01:25

Instrumentation Amplifier

434
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...
434
Electrocardiogram01:29

Electrocardiogram

2.1K
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...
2.1K
Classification of Signals01:30

Classification of Signals

381
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
381
Convolution: Math, Graphics, and Discrete Signals01:24

Convolution: Math, Graphics, and Discrete Signals

223
In any LTI (Linear Time-Invariant) system, the convolution of two signals is denoted using a convolution operator, assuming all initial conditions are zero. The convolution integral can be divided into two parts: the zero-input or natural response and the zero-state or forced response, with t0 indicating the initial time.
To simplify the convolution integral, it is assumed that both the input signal and impulse response are zero for negative time values. The graphical convolution process...
223

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

DataAtlas: automatic generation of data dictionaries using large language models.

JAMIA open·2026
Same author

Genomic characterisation of the outbreak-associated hantavirus strain.

Infectious diseases (London, England)·2026
Same author

Integrated Downstream Analysis and Epidemiological Modelling of Hantavirus Infection: From Host Transcriptomics to Transmission Dynamics.

Pathogens (Basel, Switzerland)·2026
Same author

Integrated Evolutionary and Multi-Omic Analysis of STAT Family Activation Across Solid Tumors.

Genes·2026
Same author

An Innovative 3D Slicer Plugin for Brain Images Annotation and Lesions Study.

Studies in health technology and informatics·2026
Same author

On the Ethical Aspect of Artificial Intelligence-Based Decision Process for Transplantation.

Studies in health technology and informatics·2026
Same journal

Novel Parent Survey Measures Sensory Behaviors Incorporating Sensory Modality and Stimulus Intensity.

Heliyon·2026
Same journal

Expression of concern: "SQSTM1/p62 promotes the progression of gastric cancer through epithelial-mesenchymal transition" [Heliyon 10 (2024) e24409].

Heliyon·2026
Same journal

Expression of concern: "TL1A promotes metastasis and EMT process of colorectal cancer" [Heliyon 10 (2024) e24392].

Heliyon·2026
Same journal

Expression of concern: "Factors affecting timing of surgery following neoadjuvant chemoradiation for esophageal cancer" [Heliyon 9 (2023) e23212].

Heliyon·2026
Same journal

Expression of concern: "On stratified single-valued soft topogenous structures" [Heliyon 10 (2024) e27926].

Heliyon·2026
Same journal

Expression of concern: "Artifact removal and motor imagery classification in EEG using advanced algorithms and modified DNN" [Heliyon 10 (2024) e27198].

Heliyon·2026
查看所有相关文章

相关实验视频

Updated: May 29, 2025

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

1.7K

一个卷积自编码器框架用于ECG信号分析.

Ugo Lomoio1, Patrizia Vizza1, Raffaele Giancotti1

  • 1Department of Surgical and Medical Sciences, University of Catanzaro, Catanzaro, Italy.

Heliyon
|February 3, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种卷积自编码器 (CAE) 框架,用于分析心电图 (ECG) 信号并识别异常. 该系统有效地检测心脏风险和病理,帮助医生进行诊断.

关键词:
异常检测检测异常检测自动编码器自动编码器决策支持系统 决策支持系统这是一个ECGECGECGECGECG.信号注释 信号注释

更多相关视频

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

942
Computer-based Multitaper Spectrogram Program for Electroencephalographic Data
04:13

Computer-based Multitaper Spectrogram Program for Electroencephalographic Data

Published on: November 13, 2019

12.0K

相关实验视频

Last Updated: May 29, 2025

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

1.7K
Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

942
Computer-based Multitaper Spectrogram Program for Electroencephalographic Data
04:13

Computer-based Multitaper Spectrogram Program for Electroencephalographic Data

Published on: November 13, 2019

12.0K

科学领域:

  • 心脏病学 心脏病学
  • 生物医学工程 生物医学工程
  • 人工智能的人工智能

背景情况:

  • 电心电图 (ECG) 信号对于评估心脏活动和检测异常至关重要.
  • 对心电图信号的自动分析,特别是长期监测和医生支持,需要可靠的系统.
  • 深度学习,特别是自动编码器 (AEs),提供了先进的方法来分析时间变化的信号,如ECG.

研究的目的:

  • 提出基于卷积自编码器 (CAE) 的框架,用于ECG信号分析和异常识别.
  • 开发一个系统,支持医生通过自动化心电图分析来诊断心脏风险和病理.
  • 为了提高异常检测系统的解释性和稳定性.

主要方法:

  • 使用卷积自编码器 (CAE),一个专门的信号数据深度神经网络,用于心电图分析.
  • 培训CAE框架对合成心电图数据进行异常检测.
  • 测试和验证基于12个导向ECG基准数据集和现实世界的场景的框架.

主要成果:

  • 基于CAE的框架在识别ECG信号中的异常方面表现出很高的准确性.
  • 在模拟测试组中达到97.82%的ROC AUC,在真实测试组中达到99.75%.
  • 该系统的可解释性模块,基于重建错误,并通过专家注释验证,证明了其有效性.

结论:

  • 拟议的基于CAE的框架提供了一个强大的工具,用于自动检测ECG信号中的异常.
  • 该系统有效地支持医生在诊断心脏病的决策过程中.
  • 解释性和预处理模块的整合提高了心电图分析系统的临床实用性和可靠性.