多普勒超声腕桡动脉血流信号对三种健康人的鉴别分析

Kuanquan Wang, Chao Xu, Dongyu Zhang, Naimin Li
{"title":"多普勒超声腕桡动脉血流信号对三种健康人的鉴别分析","authors":"Kuanquan Wang, Chao Xu, Dongyu Zhang, Naimin Li","doi":"10.1109/CBMS.2008.57","DOIUrl":null,"url":null,"abstract":"Doppler ultrasound blood flow signal (DUBFS) is a non-stationary signal that is widely used in the study of the clinical diagnosis of cardiovascular diseases. According to the theory of pulse diagnosis of traditional Chinese medicine, in this paper, a feature extraction method based on Hilbert_Huang transform is proposed in order to investigate the relationship between the DUBFS of wrist radial artery and the pathological changes of certain organs. The extracted features have applied in classification experiments on 4 groups of data, which are healthy persons, gastritis patients, cholecystitis patients and nephritis patients, respectively. Experimental results with high recognition rates demonstrate that Hilbert_Huang transform is an effective method of time-frequency analysis for DUBFS, and extracted features by proposed method have promising discriminating ability between the healthy people and 3 kinds of patients.","PeriodicalId":377855,"journal":{"name":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Analysis of Doppler Ultrasound Blood Flow Signals of Wrist Radial Artery for Discriminating Healthy People from 3 Kinds of Patients\",\"authors\":\"Kuanquan Wang, Chao Xu, Dongyu Zhang, Naimin Li\",\"doi\":\"10.1109/CBMS.2008.57\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Doppler ultrasound blood flow signal (DUBFS) is a non-stationary signal that is widely used in the study of the clinical diagnosis of cardiovascular diseases. According to the theory of pulse diagnosis of traditional Chinese medicine, in this paper, a feature extraction method based on Hilbert_Huang transform is proposed in order to investigate the relationship between the DUBFS of wrist radial artery and the pathological changes of certain organs. The extracted features have applied in classification experiments on 4 groups of data, which are healthy persons, gastritis patients, cholecystitis patients and nephritis patients, respectively. Experimental results with high recognition rates demonstrate that Hilbert_Huang transform is an effective method of time-frequency analysis for DUBFS, and extracted features by proposed method have promising discriminating ability between the healthy people and 3 kinds of patients.\",\"PeriodicalId\":377855,\"journal\":{\"name\":\"2008 21st IEEE International Symposium on Computer-Based Medical Systems\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 21st IEEE International Symposium on Computer-Based Medical Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CBMS.2008.57\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBMS.2008.57","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

多普勒超声血流信号(DUBFS)是一种非平稳信号,广泛应用于心血管疾病的临床诊断研究。本文根据中医脉诊理论,提出了一种基于Hilbert_Huang变换的特征提取方法,探讨腕桡动脉DUBFS与某些脏器病理变化的关系。将提取的特征分别应用于健康人、胃炎患者、胆囊炎患者和肾炎患者4组数据的分类实验。实验结果表明,Hilbert_Huang变换是一种有效的DUBFS时频分析方法,具有较高的识别率,所提方法提取的特征对健康人群和3种患者具有良好的区分能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Analysis of Doppler Ultrasound Blood Flow Signals of Wrist Radial Artery for Discriminating Healthy People from 3 Kinds of Patients
Doppler ultrasound blood flow signal (DUBFS) is a non-stationary signal that is widely used in the study of the clinical diagnosis of cardiovascular diseases. According to the theory of pulse diagnosis of traditional Chinese medicine, in this paper, a feature extraction method based on Hilbert_Huang transform is proposed in order to investigate the relationship between the DUBFS of wrist radial artery and the pathological changes of certain organs. The extracted features have applied in classification experiments on 4 groups of data, which are healthy persons, gastritis patients, cholecystitis patients and nephritis patients, respectively. Experimental results with high recognition rates demonstrate that Hilbert_Huang transform is an effective method of time-frequency analysis for DUBFS, and extracted features by proposed method have promising discriminating ability between the healthy people and 3 kinds of patients.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Decision Support for Alzheimer's Patients in Smart Homes A Telemedicine Network Using Secure Techniques and Intelligent User Access Control MapFace - An Editor for MetaMap Transfer (MMTx) Asynchronous Data Replication: A National Integration Strategy for Databases on Telemedicine Network Sentiment in Science - A Case Study of CBMS Contributions in Years 2003 to 2007
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1