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

Instrumentation Amplifier01:25

Instrumentation Amplifier

464
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...
464
Electrocardiogram01:29

Electrocardiogram

2.2K
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...
2.2K
Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

543
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...
543

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

Right Ventricular to Pulmonary Artery Coupling and Clinical Outcomes after Interatrial Shunting in Heart Failure: Exploratory Analysis of the PRELIEVE study.

ESC heart failure·2026
Same author

Cardiac Arrest as the First Manifestation of Single Coronary Artery-Potential Role of FFR<sub>CT</sub> for Detecting Critical Flow Reduction. A Case Report.

Clinical case reports·2026
Same author

Imaging and biomarker-based risk stratification in TAVI: the role of epicardial fat, visceral fat, and adiponectin.

European heart journal open·2026
Same author

First-in-human experience with a heterotopic cross-caval transcatheter tricuspid valve replacement.

EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology·2026
Same author

Safety and Efficacy of a Novel Atrial Flow Regulator in Patients With Severe Pulmonary Arterial Hypertension: The AFR-Prophet Study.

Journal of the Society for Cardiovascular Angiography & Interventions·2026
Same author

Pentaphosphorylated magic spot nucleotides: chemoenzymatic synthesis and disassembly-based sensing.

Organic & biomolecular chemistry·2026
Same journal

Systematic multi-domain screening of lead-specific electrocardiographic features associated with sudden cardiac death.

Journal of electrocardiology·2026
Same journal

The need to measure electrical synchrony - Assessment of electrical synchrony and its utility. Synchromax in real life.

Journal of electrocardiology·2026
Same journal

An assessment of intern doctors' experiences of undergraduate education in electrocardiogram interpretation.

Journal of electrocardiology·2026
Same journal

Feasibility and efficacy of left bundle branch area pacing guided by modified chest lead 1.

Journal of electrocardiology·2026
Same journal

Spatial proximity or vector orientation? Re-evaluating ECG interpretation in anterior myocardial infarction using cardiac magnetic resonance.

Journal of electrocardiology·2026
Same journal

Pacing spikes without visible QRS complexes: Failure to capture?

Journal of electrocardiology·2026
查看所有相关文章

相关实验视频

Updated: Jun 13, 2025

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System
10:17

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System

Published on: April 11, 2025

434

使用人工智能进行高精度心电图数字化.

Anthony Demolder1, Viera Kresnakova2, Michal Hojcka3

  • 1Powerful Medical, Bratislava, Slovakia; Cardiovascular Centre Aalst, Aalst, Belgium.

Journal of electrocardiology
|February 26, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种自动化的深度学习方法,用于从图像中数字化心电图 (ECG),实现高精度并克服现实世界的质量问题. 该系统允许使用智能手机进行快速,可访问的ECG分析.

关键词:
人工智能的人工智能是人工智能.数字信号 数字信号 数字信号电子图形数字化ECG数字化电脑心电图像图像 电脑心电图像图像高精度高精度的高精度纸张ECG ECG 这是一张纸.

更多相关视频

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

3.6K
Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function
05:03

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

Published on: December 11, 2019

8.6K

相关实验视频

Last Updated: Jun 13, 2025

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System
10:17

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System

Published on: April 11, 2025

434
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

3.6K
Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function
05:03

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

Published on: December 11, 2019

8.6K

科学领域:

  • 生物医学工程 生物医学工程
  • 医疗保健中的人工智能
  • 数字健康数字健康

背景情况:

  • 传统的心电图 (ECG) 数字化在图像质量和手动输入方面面临着挑战.
  • 数字化纸张ECG对于保存,传输和高级分析至关重要.

研究的目的:

  • 开发一种基于深度学习的全自动化解决方案,用于高精度的心电图数字化.
  • 解决现有方法在现实世界存在的局限性,可变质量的心电图像.

主要方法:

  • 一种涉及图像规范化,网格检测,扭曲纠正和信号重建的深度学习方法.
  • 使用PMcardio ECG图像数据库 (PM-ECG-ID) 采用6000个不同的心电图像.
  • 使用皮尔森相关系数 (PCC),RMSE和SNR评估的性能.

主要成果:

  • 取得的平均PCC>0.91,SNR>12.5dB,以及RMSE<0.10mV.
  • 数字化时间始终在7秒以下.
  • 在低分辨率和图像退化等具有挑战性的条件下强大的性能,故障率为6.62%.

结论:

  • 深度学习方法提供了高精度的ECG数字化,克服了实际挑战.
  • 通过智能手机实现全自动化数字化,提高了用于人工智能驱动分析的ECG数据可访问性.