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相关概念视频

Electrocardiogram Fundamentals01:28

Electrocardiogram Fundamentals

502
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...
502
Pulse rhythm01:30

Pulse rhythm

758
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...
758
Electrocardiogram01:29

Electrocardiogram

2.2K
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...
2.2K
ECG Interpretation of Rhythms01:24

ECG Interpretation of Rhythms

471
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....
471
Disturbances in Heart Rhythm01:28

Disturbances in Heart Rhythm

895
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...
895
Holter Monitor: 24-Hour Monitoring01:23

Holter Monitor: 24-Hour Monitoring

1
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...
1

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相关实验视频

Updated: Jun 3, 2025

Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function
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研究一种基于知识蒸的轻量化心律失常分类模型,用于可穿戴单线心电图监测系统.

Xiang An1, Shiwen Shi1, Qian Wang1

  • 1Academy of Artificial Intelligence, Beijing Institute of Petrochemical Technology, Beijing 102617, China.

Sensors (Basel, Switzerland)
|January 8, 2025
PubMed
概括

本研究引入了一种轻量级的深度学习模型,用于使用心电图 (ECG) 信号实时检测心律失常. 这种高效的模型能够在可穿戴设备上准确地分析心律,从而提高了疾病诊断的可访问性.

关键词:
心律失常的分类是心律失常的分类.边缘情报 边缘情报 边缘情报电心电图 (ECG) 是一种心电图.嵌入式系统嵌入式系统知识蒸 (KD) 是指知识的蒸.微控制器上的微控制器

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相关实验视频

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Analyzing Long-Term Electrocardiography Recordings to Detect Arrhythmias in Mice
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Real-Time Electrocardiogram Monitoring During Treadmill Training in Mice
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科学领域:

  • 生物医学工程 生物医学工程
  • 医疗保健中的人工智能
  • 心脏病学 心脏病学

背景情况:

  • 节律失常构成严重的全球健康风险,需要持续的心电图 (ECG) 监测,用于早期诊断和干预.
  • 目前用于自动检测心律失常的深度学习模型虽然有效,但对于资源有限的可穿戴设备来说往往过于复杂.

研究的目的:

  • 开发一种高效,轻量级的深度学习模型,用于适合于可穿戴设备中嵌入智能的心律失常分类.
  • 在小型便携式系统上实现实时ECG监测和分析.

主要方法:

  • 一种知识蒸技术被用来从一个更大的"老师"模型中训练一个紧的"学生"模型.
  • 这种轻量级模型是在使用STM32F429发现套件和ADS1292R芯片的可穿戴心电图监测系统上实现的.

主要成果:

  • 学生模型的准确性达到96.32%,与教师模型相比.
  • 该型号的压缩比为1242.58倍,超过了其他轻型型号.
  • 在开发的可穿戴系统上成功实现了实时心律失常检测.

结论:

  • 拟议的轻量级模型为设备上的心律失常检测提供了有效的解决方案,克服了复杂的深度学习模型的局限性.
  • 这一进步有助于在可穿戴技术中部署复杂的AI驱动的心脏监测.