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

Pulse rhythm01:30

Pulse rhythm

852
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...
852
Correlation between ECG and Cardiac Cycle01:25

Correlation between ECG and Cardiac Cycle

7.4K
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...
7.4K
ECG Interpretation of Rhythms01:24

ECG Interpretation of Rhythms

1.6K
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....
1.6K

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

Elucidating Genetic Drivers of Chronic Inflammation in Obesity.

Biomedicines·2026
Same author

Computational Advances in Taste Perception: From Ion Channels and Taste Receptors to Neural Coding.

Brain sciences·2026
Same author

Using Machine Learning Methods to Predict Cognitive Age from Psychophysiological Tests.

Healthcare (Basel, Switzerland)·2025
Same author

Spiral attractors in a reduced mean-field model of neuron-glial interaction.

Chaos (Woodbury, N.Y.)·2024
Same author

Artificial Neural Network Model with Astrocyte-Driven Short-Term Memory.

Biomimetics (Basel, Switzerland)·2023
Same author

Model of Neuromorphic Odorant-Recognition Network.

Biomimetics (Basel, Switzerland)·2023

相关实验视频

Updated: Jul 27, 2025

Asthma Detection Research Based on Voice Signal Processing and Machine Learning
04:04

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

7

使用机器学习算法通过心律图来确定一个人的COVID后状态.

Sergey V Stasenko1, Andrey V Kovalchuk2, Evgeny V Eremin3

  • 1Neurotechnology Department, Institute of Biology and Biomedicine, Lobachevsky State University of Nizhny Novgorod, 603022 Nizhny Novgorod, Russia.

Sensors (Basel, Switzerland)
|June 10, 2023
PubMed
概括
此摘要是机器生成的。

研究人员开发了一种新方法,使用心电图 (ECG) 数据来检测COVID后的疾病. 这项技术可以识别"心脏",可能标记COVID-19.

关键词:
在 COVID-19 疫情中,数据分析数据分析数据分析电心电图 (ECG) 是一种心电图.机器学习算法的算法在COVID后的状态.

更多相关视频

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

4.5K
Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
10:28

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

Published on: July 24, 2019

15.2K

相关实验视频

Last Updated: Jul 27, 2025

Asthma Detection Research Based on Voice Signal Processing and Machine Learning
04:04

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

7
Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface
11:54

Real-Time Proxy-Control of Re-Parameterized Peripheral Signals using a Close-Loop Interface

Published on: May 8, 2021

4.5K
Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
10:28

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

Published on: July 24, 2019

15.2K

科学领域:

  • 心脏病学 心脏病学
  • 医疗技术 医疗技术 医学技术
  • 传染性疾病 传染性疾病

背景情况:

  • 后COVID条件影响心脏功能,需要可靠的检测方法.
  • 电心电图 (ECG) 数据为心律调节提供了一个非侵入性的窗口.
  • 当前的诊断工具可能无法完全捕捉COVID后心脏变化的细微差别.

研究的目的:

  • 引入一种新的方法,使用心电图来检测COVID后的疾病.
  • 为了识别特定的心电图标记,称为"心脏",表明过去的COVID-19感染.
  • 探索这些心脏的潜力,作为COVID特异性心律调节的客观标记.

主要方法:

  • 利用卷积神经网络 (CNN) 来分析心电图数据.
  • 开发了一种检测算法,用于识别COVID后患者的"心脏".
  • 进行了血液参数测量,并为康复的COVID-19患者创建了个人资料.

主要成果:

  • 在测试样本中检测心脏的准确率达到了87%.
  • 证实心脏是固有的生理信号,而不是硬件工件.
  • 在康复患者中,ECG发现与血液参数概况之间建立了相关性.

结论:

  • 这种基于CNN的新方法有效地检测心脏,表明COVID后的心脏变化.
  • 心脏杆显示出作为可靠的生物标志物对COVID-19对心律的影响有前途.
  • 这些发现支持开发用于COVID-19诊断和监测的远程查工具.