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Pulse rhythm01:30

Pulse rhythm

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 muscle...
Imaging Studies for Cardiovascular System I:Echocardiography01:17

Imaging Studies for Cardiovascular System I:Echocardiography

Cardiac imaging studies encompass a wide range of noninvasive and minimally invasive techniques designed to visualize the heart's structure and function in detail. One such technique is echocardiography, which uses high-frequency ultrasound waves to produce detailed images of the heart, known as echocardiograms.
Indications: Echocardiography is utilized to diagnose heart failure, valve disorders, and myocardial infarction. It also assesses cardiac structures' size, shape, and motion, evaluates...

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相关实验视频

Updated: Jul 20, 2026

Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph
05:32

Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph

Published on: February 21, 2025

基于雷达的生命信号检测系统的心脏活动的胸壁运动模型.

Shaocan Fan1, Zhenmiao Deng1

  • 1School of Electronics and Communication Engineering, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518107, China.

Sensors (Basel, Switzerland)
|April 13, 2024
PubMed
概括

研究人员开发了一种新模型来模拟心跳诱导的胸壁运动 (CWM) 数据. 这种方法解决了雷达数据集的稀缺性,使得深度学习在非接触式生命体征检测方面的进步成为可能.

科学领域:

  • 生物医学工程 生物医学工程
  • 信号处理 信号处理
  • 人工智能的人工智能

背景情况:

  • 基于雷达的非接触式生命体征检测越来越多地使用深度学习.
  • 雷达数据集的有限可用性阻碍了深度学习模型的开发.
  • 用于雷达检测生命体征的数据采集和标记是复杂的,需要专门的资源.

研究的目的:

  • 为模拟心跳诱导的胸壁运动 (CWM) 提出一种新型模型.
  • 创建一个大数据集,用于训练基于雷达的生命体征检测的深度学习模型.
  • 为了克服稀缺的局限性,现实世界的雷达数据.

主要方法:

  • 分析了VICON红外 (IR) 运动捕捉和连续波 (CW) 雷达数据的CWM在呼吸保持期间.
  • 在心脏循环阶段中识别和数学建模运动特征.
  • 利用心跳的生理特性来告知数学函数选择.

主要成果:

  • 开发的模型产生了与测量CWM数据密切匹配的模拟数据.
  • 使用动态时间扭曲 (DTW) 和根平均平方误差 (RMSE) 的验证证实了数据的真实性.
  • 模型参数可以调整,以模拟不同个体的心跳信号.
关键词:
在CWM模型中,CWM模型是这是一个多普勒雷达雷达.数据数据的数据数据的数据.心跳的心跳的心跳无接触式监控是指非接触式监控.

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Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System
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Evaluation of Right Ventricular Function in Experimental Models of Pulmonary Arterial Hypertension
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Evaluation of Right Ventricular Function in Experimental Models of Pulmonary Arterial Hypertension

Published on: June 27, 2025

相关实验视频

Last Updated: Jul 20, 2026

Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph
05:32

Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph

Published on: February 21, 2025

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System
10:17

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System

Published on: April 11, 2025

Evaluation of Right Ventricular Function in Experimental Models of Pulmonary Arterial Hypertension
10:03

Evaluation of Right Ventricular Function in Experimental Models of Pulmonary Arterial Hypertension

Published on: June 27, 2025

结论:

  • 该CWM模拟模型有效地为深度学习生成现实的数据.
  • 这便于在基于雷达的非接触式生命体征检测中应用数据驱动的方法.
  • 预计这种方法将加速该领域的研发.