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相关概念视频

Electrocardiogram01:29

Electrocardiogram

2.3K
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...
2.3K
Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

600
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...
600
Instrumentation Amplifier01:25

Instrumentation Amplifier

521
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...
521
ECG Interpretation of Rhythms01:24

ECG Interpretation of Rhythms

932
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....
932
Correlation between ECG and Cardiac Cycle01:25

Correlation between ECG and Cardiac Cycle

5.4K
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...
5.4K
Pulse rhythm01:30

Pulse rhythm

803
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...
803

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相关实验视频

Updated: Jul 5, 2025

Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice
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Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice

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用于分析心电图 (ECG) 信号的预处理技术和人工智能算法:全面审查

Muhammad Farhan Safdar1, Robert Marek Nowak1, Piotr Pałka2

  • 1Institute of Computer Science, Faculty of Electronics and Information Technology, Warsaw University of Technology, 00-665 Warsaw, Poland.

Computers in biology and medicine
|January 13, 2024
PubMed
概括

人工智能 (AI) 显著增强了心电图 (ECG) 分析,深度学习和变压器模型达到高达98%的准确性. 可穿戴设备为人工智能校准提供方便,准确的远程监控.

关键词:
基于代理人的建模.数据增强数据增强深度学习是一种深度学习.电心电图 电心电图 电心电图谱图谱图谱图谱图谱图谱图谱图谱图谱图谱可穿戴设备是可以穿戴的.

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Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis
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Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography
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Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis
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Microstate and Omega Complexity Analyses of the Resting-state Electroencephalography
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科学领域:

  • 心脏病学和生物医学工程
  • 医疗保健中的人工智能
  • 信号处理 信号处理

背景情况:

  • 电心电图 (ECG) 信号对于评估心脏电活动至关重要.
  • 在过去的十年中,人工智能方法,包括机器学习 (ML) 和深度学习 (DL),已经推进了ECG分析.
  • 传统的信号处理方法正在以人工智能驱动的方法发展.

研究的目的:

  • 从2012年到2022年,审查AI在ECG信号分析中的应用.
  • 将心电图分析方法,数据源和新兴趋势分类.
  • 评估不同人工智能模型所取得的性能和准确性改进.

主要方法:

  • 对用于心电图分析的AI技术的审查,将它们分类为经典信号处理,ML和DL (递归模型,变压器,混合模型).
  • 数据来源的分析,包括医院机器和可穿戴设备,以及基准数据集 (例如,Physio-Net,MIT-BIH,PTB).
  • 包括新的趋势,如先进的预处理,数据增强,模拟和基于代理的建模.

主要成果:

  • 归因于ML,DL,混合型和变压器模型的ECG分析精度的显著改善,变压器的精度达到98%.
  • 卷积神经网络和混合模型表现出高效率.
  • 可穿戴设备显示持续监控和AI模型校准的希望,达到82%-83%的准确性.
  • 通过里埃和波形变换生成光谱图,准确度为90%-95%;几何数据增强是有效的,但提取/连锁方法需要进一步开发.
  • 基于代理的建模和模拟被审查用于心血管风险评估.

结论:

  • 人工智能,特别是DL和变压器模型,已经大大提高了ECG分析的准确性和复杂性.
  • 与人工智能集成的可穿戴技术为远程心脏监测和人工智能模型改进提供了可行的,可访问的选择.
  • 先进的信号处理和数据增强技术是加强心电图分析的关键,模拟方法为风险预测提供了潜力.