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相关概念视频

Dysrhythmias V: Evaluating Dysrhythmias01:30

Dysrhythmias V: Evaluating Dysrhythmias

41
Dysrhythmias, also known as arrhythmias, are disturbances in the heart's rhythm that range from benign to life-threatening. A thorough evaluation is crucial for appropriate management and involves a comprehensive medical history, physical examination, and various diagnostic tests.Medical HistorySymptoms: Collect detailed information on palpitations, dizziness, syncope, chest pain, and fatigue. Note their onset, frequency, and triggers.Previous Cardiac Issues: Document any history of heart...
41
Disturbances in Heart Rhythm01:28

Disturbances in Heart Rhythm

997
Arrhythmia or dysrhythmia refers to an abnormal heart rhythm caused by a defect in the heart's conduction system. It can cause the heart to beat irregularly, too quickly, or too slowly, leading to symptoms like chest pain, shortness of breath, and fainting. Factors such as stress, caffeine, alcohol, nicotine, cocaine, certain drugs, congenital defects, diseases, and electrolyte abnormalities can trigger arrhythmias.
Arrhythmias are categorized by their speed, rhythm, and origin. A slow...
997
Dysrhythmias II: Classification of Tachyarrhythmias01:28

Dysrhythmias II: Classification of Tachyarrhythmias

10
Tachyarrhythmias are a type of dysrhythmia where the heart rate exceeds 100 beats per minute. Here are some common types of tachyarrhythmias:Sinus TachycardiaSinus tachycardia originates from increased impulses from the sinus node, leading to an elevated heart rate. It is often triggered by stress, fever, or exercise.Patients may experience palpitations, a sensation of a racing heart, dizziness, and chest discomfort.Causes and Risk Factors: Common causes include physical exertion, emotional...
10
Mechanism of Cardiac Arrhythmias01:28

Mechanism of Cardiac Arrhythmias

943
Arrhythmias are irregular heart rhythms occurring when the heart's electrical impulses become abnormal. These disturbances can lead to various symptoms, depending on their severity and the underlying cause. Some common factors contributing to arrhythmias include hypoxia, ischemia, electrolyte imbalances, excessive catecholamine exposure, drug toxicity, and muscle overstretching. Arrhythmias can be classified into two main types based on the rate and site of origin of abnormal heart rhythms.
943
ECG Interpretation of Arrhythmias II: Atrial, Junctional and Ventricular Arrhythmias01:25

ECG Interpretation of Arrhythmias II: Atrial, Junctional and Ventricular Arrhythmias

33
Arrhythmia is a condition characterized by an irregular heart rhythm, with ECG changes that differ based on its origin and nature. The types of arrhythmias discussed below include atrial, junctional, and ventricular arrhythmias.Atrial ArrhythmiasPremature Atrial Complexes (PACs): PACs are early atrial beats caused by stress, caffeine, alcohol, electrolyte imbalances, hypoxia, hyperthyroidism, or certain medications (e.g., bronchodilators and decongestants). The ECG shows early P waves with an...
33
Dysrhythmias I: Introduction01:15

Dysrhythmias I: Introduction

14
Dysrhythmias refers to abnormalities in the heart's rhythm. They result from disruptions in the heart's electrical conduction system, which includes the sinoatrial(SA)node, atrioventricular(AV) node, the bundle of His, bundle branches, and Purkinje fibers.Definition and PathophysiologyDysrhythmias result from disorders of impulse formation, impulse conduction, or both. The heart contains specialized cells in the sinoatrial node, atrioventricular node, and the bundle of His and Purkinje fibers...
14

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Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice
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基于多个心电图数据库的心律失常分类检测.

Meng Qi1,2, Hongxiang Shao1,2, Nianfeng Shi1,2

  • 1Computer and Information Engineering Department, Luoyang Institute of Science and Technology, Luoyang, China.

PloS one
|September 27, 2023
PubMed
概括
此摘要是机器生成的。

本研究介绍了Hercules-3,一个统一的心电图 (ECG) 心律失常数据库,解决了用于训练神经网络的数据限制. 新的数据库显著改善了心律失常的分类性能.

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科学领域:

  • 心脏病学 心脏病学
  • 生物医学工程 生物医学工程
  • 机器学习 机器学习

背景情况:

  • 心血管疾病是全球主要的死亡原因之一.
  • 电心电图 (ECG) 对于非侵入性心脏病检测至关重要.
  • 现有的心电图数据库受到有限的样本大小和不平衡的分布的影响,阻碍了有效的神经网络训练.

研究的目的:

  • 为了解决机器学习ECG数据的稀缺性和不平衡性.
  • 开发一个统一和全面的ECG心律失常分类数据库.
  • 评估在拟议的数据库上训练的神经网络的性能.

主要方法:

  • 深入分析了三个精细标记的心电图数据库.
  • 用一致的采样频率提取和统一心跳.
  • 开发一种对心跳进行自我处理的方法.
  • 形成赫拉克勒斯-3统一的ECG心律失常分类数据库 (80%的培训,20%的测试).

主要成果:

  • 在赫拉克勒斯-3上训练的完全连接的神经网络实现了98.67%的准确性,用于16类心律失常的分类.
  • 拟议的数据处理方法至少提高了6%的分类回忆.
  • 与其他方法相比,在分类准确度 (≥4%) 和F1得分 (≥7%) 中观察到显著的改善.

结论:

  • 赫拉克勒斯-3数据库为ECG心律失常分类挑战提供了强大的解决方案.
  • 对心跳的自我处理方法在改善分类指标方面是有效的.
  • 这项工作有助于开发更实用,更有效的神经网络模型,用于心脏诊断.