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相关概念视频

Disturbances in Heart Rhythm01:28

Disturbances in Heart Rhythm

956
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...
956

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Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation
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一个新的心房动自动检测算法,基于集体学习和多特征歧视.

Xiangkui Wan1,2, Yizheng Liu1, Xiaoyu Mei1

  • 1Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy and Operation Control of Energy Storage System, Hubei University of Technology, Wuhan, 430068, People's Republic of China.

Medical & biological engineering & computing
|February 22, 2024
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概括

一个新的算法,集体学习和多特征歧视 (ELMD),使用短心电图 (ECG) 信号准确检测心房动 (AF). 这种方法提高了可穿戴设备的检测效率.

关键词:
检测心房动的检测方法电心电图 (ECG) 是一种心电图.组合学习学习 组合学习多功能提取多功能提取

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High-Resolution Endocardial and Epicardial Optical Mapping in a Sheep Model of Stretch-Induced Atrial Fibrillation
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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
  • 信号处理 信号处理

背景情况:

  • 前庭动 (AF) 诊断需要长时间的心电图 (ECG) 数据,限制检测效率.
  • 在简短的心电图记录中自动检测AF是一个重大挑战.

研究的目的:

  • 提出一个新的算法,集体学习和多特征歧视 (ELMD),以有效识别和检测AF信号.
  • 为了快速区分AF事件,使用短时间,单线心电图数据.

主要方法:

  • 使用集体学习构建了一个BSK模型分类器.
  • 检测到的ECG R波和细分信号到RR间隔.
  • 从RR间隔中提取时间,频率和非线性特征,用于BSK模型的歧视.

主要成果:

  • 在使用RR间隔的长期心电图数据中实现了>99%的AF检测特异性和准确性.
  • 在测试心脏段时,达到>96%的灵敏度和准确性.
  • 启用精确的AF事件识别,至少有四个心脏段.

结论:

  • 该ELMD算法促进了实时和准确的AF检测.
  • 这种方法适用于像可穿戴设备这样的低计算功率设备.
  • 与AF检测的传统单模分类方法相比,显著改进.