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相关概念视频

Pulse rhythm01:30

Pulse rhythm

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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...
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Assessing Blood pressure using a doppler ultrasound01:19

Assessing Blood pressure using a doppler ultrasound

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To obtain accurate blood pressure measurements in clinical settings, especially when traditional methods are insufficient, healthcare professionals utilize the Doppler ultrasound technique. This method uses high-frequency sound waves to detect blood flow within the arteries, which is crucial for patients with conditions that complicate circulatory system assessment.
Pre-Procedural Guidelines for Doppler Ultrasound Blood Pressure Assessment:
Preparation of Equipment:
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相关实验视频

Updated: Jan 18, 2026

Real-Time Cardiac Mapping with a Noninvasive Imageless Electrocardiographic Imaging System
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使用FMCW雷达通过新型信号处理算法进行非接触式心率变化监测.

Guangyu Cui1, Yujie Wang1, Xinyi Zhang1

  • 1School of Information and Communication Engineering, North University of China, Taiyuan 030051, China.

Sensors (Basel, Switzerland)
|September 13, 2025
PubMed
概括

这项研究引入了一种使用毫米波雷达的新型非接触式心率变化 (HRV) 传感方法. 新的算法显著减少了节拍间隔估计错误,改善了心血管健康监测.

关键词:
心率变化 (HRV) 是指心率的变化.毫米波 (mmWave) 无线电波的使用无接触式监控是指非接触式监控.频谱稀疏分离算法

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Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation
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Calculating Heart Rate Variability from ECG Data from Youth with Cerebral Palsy During Active Video Game Sessions
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科学领域:

  • 生物医学工程 生物医学工程
  • 信号处理 信号处理
  • 心血管健康 心血管健康

背景情况:

  • 心率变化 (HRV) 是自主神经系统和心血管健康的关键指标.
  • 对于HRV而言,非接触式监测方法对于用户的舒适性和长期坚持是非常理想的.
  • 现有的非接触式HRV传感技术在准确性和可扩展性方面面临挑战.

研究的目的:

  • 开发和验证一种新的算法,用于使用频率调制连续波 (FMCW) 毫米波雷达进行准确的HRV提取.
  • 通过分离心脏和呼吸道信号,使HRV的稳健,非接触测量成为可能.
  • 改进现有的节拍间隔 (IBI) 估计方法.

主要方法:

  • 开发了一个无校准的3D目标定位模块,集成了数字光束成型,移动目标指示和DBSCAN集群.
  • 建立了基于阶段的数学模型,以系统地分离呼吸和心脏振动.
  • 使用拉格朗的倍数实现了第二阶段光谱稀疏分离算法,以实现强大的心跳提取.

主要成果:

  • 与最先进的方法相比,拟议的算法实现了平均节拍间隔 (IBI) 估计误差的50%以上的减少.
  • 在各种测试场景中保持一致的准确性.
  • 该方法成功识别了心跳事件,并从恢复的心脏信号中获得HRV指标.

结论:

  • 新的FMCW基于雷达的算法为准确的HRV评估提供了一个有前途的非接触式方法.
  • 这种方法有可能通过可扩展,用户友好的技术来增强心血管健康监测.
  • 需要进一步的研究来解决对象运动和实时应用的局限性.