自动心律失常检测技术:对前性方法的全面审查
1Department of Electronics & Communication Engineering, Indian Institute of Information Technology Bhagalpur, India.
概括
使用机器学习和深度学习技术自动检测心律失常对于早期诊断心律不规则至关重要. 本综述对现有方法进行了分类,突出了它们的性能依赖性以及在ECG分析中需要改进的领域.
科学领域:
- 心脏病学 心脏病学
- 生物医学工程 生物医学工程
- 人工智能的人工智能
背景情况:
- 心律失常,或心律不规律,对健康构成重大风险,包括心脏骤停.
- 使用心电图 (ECG) 分析自动检测心律失常对于及时干预至关重要.
- 现有的自动化技术主要基于机器学习和深度学习方法.
研究的目的:
- 综合审查和分类现有的自动化心律失常检测技术.
- 分析基于机器学习和深度学习的方法的优势和局限性.
- 确定未来研究和改善心律失常分类的领域.
主要方法:
- 使用主要科学数据库对自动心律失常检测技术的系统文献综述.
- 将技术分类为机器学习和深度学习方法.
- 对性能因素的分析,包括ECG预处理,特征提取和数据集分区.
主要成果:
- 机器学习技术需要特征提取,而深度学习方法通常会绕过这个步骤.
- 性能受到ECG数据质量,特征选择和数据集特征 (例如,MIT-BIH心律失常数据库) 的严重影响.
- 挑战包括处理阶级不平衡,确保跨研究公平的绩效比较.
结论:
- 机器学习和深度学习都显示出对自动心律失常检测的前景.
- 未来的研究应该专注于强大的特征工程,解决类不平衡,并利用各种ECG数据集进行验证.
- 为了可靠地比较不同的自动化技术,需要标准化的评估协议.
相关概念视频
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Introduction
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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...
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...
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