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相关概念视频

Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

602
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...
602
ECG Interpretation of Rhythms01:24

ECG Interpretation of Rhythms

976
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....
976
Classification of Signals01:30

Classification of Signals

471
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...
471
Electrocardiogram01:29

Electrocardiogram

2.4K
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...
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Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice
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强大的算法用于检测和分类具有不同形态的QRS复合体,使用连续线条波量变换与自动尺度检测.

Frank Martínez-Suárez1,2, Carlos Alvarado-Serrano1, Oscar Casas2

  • 1Bioelectronics Section, Department of Electrical Engineering, Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (CINVESTAV) , Mexico City 07360, Mexico.

Biomedical physics & engineering express
|December 18, 2023
PubMed
概括

这项研究引入了一种使用连续波束转换 (CWT) 的新型算法,用于在心电图信号中准确的QRS复合体检测和分类. 该方法在多个数据库中显示出高灵敏度和积极的预测性,证明对噪声强大,并且可以适应各种ECG特征.

关键词:
这是一个ECGECGECGECGECG.在QRS检测检测.连续的 spline 波形变换.心率是指心率是如何发生的.斯普林斯,斯普林斯,斯普林斯,斯普林斯,斯普林斯,斯普林斯,斯普林斯,斯普林斯

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科学领域:

  • 生物医学工程 生物医学工程
  • 信号处理 信号处理
  • 心脏病学 心脏病学

背景情况:

  • 准确检测和分类QRS复合物对于心电图 (ECG) 分析至关重要.
  • 现有的算法面临着噪音,工件和心率和形态变化的挑战.

研究的目的:

  • 开发和验证一个强大的算法,用于QRS复杂的检测,分类和划分,使用连续波形变换 (CWT) 与splines.
  • 评估算法在多样化和具有挑战性的心电图数据集上的性能.

主要方法:

  • 实施CWT与ECG分析的splines,允许在任何整数尺度上进行评估.
  • 一个四个阶段的QRS检测过程,包括CWT,初始检测,寻找错过的复合体和R-峰值校正.
  • 划分QRS复杂的开始和结束.

主要成果:

  • 在MIT-BIH (Se=99.72%,P+=99.87%),欧洲ST-T (Se=99.92%,P+=99.55%) 和QT (Se=99.97%,P+=99.99%) 数据库中实现了高灵敏度 (Se) 和正预测性 (P+).
  • 对于QRS开始和结束的界限标准偏差处于专家接受的公差范围内.
  • 该算法证明了对噪声,工件,基线漂移的稳定性,以及适应不同心电图特征的适应性.

结论:

  • 拟议的基于CWT的算法为QRS复杂检测,分类和划分提供了可靠和准确的方法.
  • 它的适应性和稳定性使其适合于现实世界的临床应用和各种ECG数据.
  • 算法的性能验证了CWT的有效性,用于高级ECG信号分析.