Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Cardiovascular System Abnormal Findings II: Auscultation01:25

Cardiovascular System Abnormal Findings II: Auscultation

529
Auscultation, an essential part of a heart examination, is done using a stethoscope. It provides crucial information about heart function and possible heart problems. Due to heart problems, abnormal sounds can be heard during systole or diastole. These sounds include S3 and S4 gallops, opening snaps, systolic clicks, and murmurs.
Abnormal Heart Sounds
Gallops:
529
Heart Sounds01:15

Heart Sounds

3.2K
Heart sounds are generated by the turbulence in blood flow due to the closing of heart valves. These sounds are best perceived slightly away from the valves, where the blood flow disseminates the sound.
Auscultation is the process of listening to these internal body sounds using a stethoscope. The heart produces four types of sounds, but only two—S1 and S2—can usually be heard with a stethoscope.
S1, also known as the "lub" sound, is caused by the closure of atrioventricular (A-V)...
3.2K
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
Correlation between ECG and Cardiac Cycle01:25

Correlation between ECG and Cardiac Cycle

11.6K
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...
11.6K
Assessment of the Cardiovascular System IV: Auscultation01:25

Assessment of the Cardiovascular System IV: Auscultation

1.7K
Cardiac auscultation is a clinical skill used to assess heart function and detect abnormalities. It involves listening to heart sounds at specific anatomical locations through a stethoscope.
Normal Heart Sounds
S1 (First Heart Sound)-
S1 is made by the closure of the mitral and tricuspid valves (atrioventricular valves), marking the beginning of systole.
S2 (Second Heart Sound)-
S2 is made by the closure of the aortic and pulmonic valves (semilunar valves), marking the end of the systole.
1.7K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Machine learning approaches to identify genetic markers for goat climatic adaptation.

3 Biotech·2026
Same author

Whole-genome resequencing suggests adaptive role of copy number variation regions in Indian cattle.

Tropical animal health and production·2026
Same author

Identification and Characterization of Sepsis Phenotypes in an Indian Cohort.

Critical care research and practice·2026
Same author

Comparison of ridge mapping using bone caliper, stone cast, CBCT and direct measurement in treatment planning of dental implants.

Bioinformation·2026
Same author

Marginal adaptation of zirconium dioxide crowns prepared with four different finish lines: An <i>in vitro</i> study.

Bioinformation·2026
Same author

Mapping genomic adaptation to environmental heterogeneity in Indian native goat populations through landscape genomics.

Mammalian genome : official journal of the International Mammalian Genome Society·2026

相关实验视频

Updated: Jan 9, 2026

Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections
06:22

Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections

Published on: September 19, 2025

406

基于转移学习的心脏声检测在声心图信号使用光谱图.

Pratibha Dohare1, Unmesh Shukla2, Diptadeep Bhattacharjee3

  • 1Cluster Innovation Centre, University of Delhi, Delhi, India.

Computer methods in biomechanics and biomedical engineering
|December 2, 2025
PubMed
概括

这项研究通过使用转移学习在心电图 (PCG) 信号中增强了心脏声检测. 连续波形变换 (CWT) 谱图和VGG19模型的最佳组合实现了89.44%的准确性.

关键词:
心脏声音分类心脏声音分类机器学习是机器学习.声心电图 (PHO) 是一种心电图.频谱图是指光谱图中的光谱.转移学习转移学习

更多相关视频

Asthma Detection Research Based on Voice Signal Processing and Machine Learning
04:04

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

885
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

654

相关实验视频

Last Updated: Jan 9, 2026

Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections
06:22

Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections

Published on: September 19, 2025

406
Asthma Detection Research Based on Voice Signal Processing and Machine Learning
04:04

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

885
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

654

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:

  • 心脏是异常的心脏声音,需要精确的检测.
  • 心电图 (PCG) 信号提供了有价值的诊断信息.
  • 自动检测心脏声可以提高诊断效率.

研究的目的:

  • 调查转移学习架构在PCG信号中检测心脏声的有效性.
  • 为了提高准确性,比较不同的特征提取技术和深度学习模型.
  • 为了优化信号预处理以提高声识别.

主要方法:

  • 使用第四阶段的Butterworth带通波器和Savitzky-Golay波器,对PCG信号进行排斥.
  • 使用短时间里叶变换 (STFT),Mel频 Cepstral 系数 (MFCC) 和连续波纹变换 (CWT) 来生成光谱图.
  • 培训VGG16,VGG19,ResNet50和InceptionV3模型在生成的光谱图上进行二进制分类.

主要成果:

  • 结合CWT光谱图和VGG19模型,实现了最高准确度的89.44%.
  • 优化的信号意味着显著改善了分类性能.
  • 各种光谱图和转移学习模型组合显示出卓越的精度,回忆,F1得分和ROC-AUC.

结论:

  • 转移学习架构显示出来自PCG信号的自动心脏声检测的显著前景.
  • 与VGG19等深度学习模型相结合的CWT光谱图提供了一个强大的方法.
  • 进一步的研究可以完善这些方法用于临床应用.