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相关概念视频

Electrocardiogram01:29

Electrocardiogram

5.3K
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...
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Holter Monitor: 24-Hour Monitoring01:23

Holter Monitor: 24-Hour Monitoring

2.0K
Holter monitoring is a continuous electrocardiography (ECG) recording that tracks the heart's electrical activity over an extended period, generally 24 to 48 hours. This noninvasive diagnostic tool detects irregular heart rhythms that may not be captured during a standard ECG performed in a clinical setting.DeviceThe Holter monitor is a portable, small device connected to several electrodes on the patient's chest. These electrodes detect the heart's electrical signals and transmit them to the...
2.0K
ECG Interpretation of Rhythms01:24

ECG Interpretation of Rhythms

12.4K
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....
12.4K
Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

1.4K
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...
1.4K
Correlation between ECG and Cardiac Cycle01:25

Correlation between ECG and Cardiac Cycle

11.7K
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...
11.7K
Pulse rhythm01:30

Pulse rhythm

1.3K
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...
1.3K

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Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function
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通过智能手表的心电图来估计年龄.

Azfar Adib1, Wei-Ping Zhu1, M Omair Ahmad1

  • 1Department of Electrical and Computer Engineering, Concordia University, Montreal, QC Canada.

NPJ biomedical innovations
|October 27, 2025
PubMed
概括

智能手表的心电图 (ECG) 信号可以准确估计年龄,超过临床心电图方法. 这项技术为年龄验证提供了一个保护隐私的解决方案,特别是用于在线儿童保护.

科学领域:

  • 生物医学工程 生物医学工程
  • 数字健康数字健康
  • 机器学习 机器学习

背景情况:

  • 准确的年龄估计对于年龄限制服务和在线儿童安全至关重要.
  • 传统的年龄验证方法 (身份验证,面部识别) 存在隐私和可靠性问题.
  • 电心电图 (ECG) 信号表现出年龄相关的特征,提供了一个潜在的生物识别替代方案.

研究的目的:

  • 为了研究使用智能手表衍生的心电图信号来估计年龄的可行性.
  • 开发和评估机器学习模型,使用可穿戴式心电图数据进行年龄预测.
  • 为了比较智能手表基于心电图的年龄估计与传统和临床心电图方法的性能.

主要方法:

  • 收集了来自 220 名跨越广泛年龄段的智能手表心电图的新型数据集.
  • 提取并分析了与年龄相关的生理变化相关的各种心电图特征.
  • 训练并测试多个机器学习模型来预测年龄并执行二进制年龄分类.

主要成果:

  • 在年龄估计中达到2.93年的平均绝对误差 (MAE),超过了基于心电图的临床研究.
  • 在青春期表现出高峰精度,与显著的ECG发育变化相关.
  • 在13-21岁的年龄范围内实现了对二元年龄分类的高准确性 (93-96%).
关键词:
心脏病学 心脏病学计算生物学和生物信息学

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相关实验视频

Last Updated: Jan 14, 2026

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Assessing the Accuracy of Fitness Smartwatch Data for Cardiovascular and Physical Activity Monitoring: A Validation Study in Digital Health
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结论:

  • 智能手表ECG信号为非侵入性年龄估计提供了可行且准确的方法.
  • 这种方法为传统的年龄验证技术提供了一个隐私意识的替代方案.
  • 可穿戴式心电图技术在需要可靠的年龄评估的应用中具有重大潜力,特别是在数字环境中.