基于多尺度微分算子的小波变换脉冲波形特征点检测

Qun Wang, Zhiwen Liu
{"title":"基于多尺度微分算子的小波变换脉冲波形特征点检测","authors":"Qun Wang, Zhiwen Liu","doi":"10.1109/BMEI.2009.5305400","DOIUrl":null,"url":null,"abstract":"The pulse waveform characteristic point detection is important for non-invasively detecting cardiovascular parameters. A novel designed algorithm based on wavelet transform (WT) is developed. For some pulse waveforms, characteristic points exactly correspond to the zero-crossing of a wavelet with one vanishing moment, while the others incompletely correspond to. And characteristic points also correspond to the local extrema of a wavelet with two vanishing moment. So an algorithm combining a wavelet with one vanishing moment and another one with two vanishing moment is used to improve the detection rate of characteristic points. The results show that automatic identification of characteristics points has a high rate of accuracy.","PeriodicalId":6389,"journal":{"name":"2009 2nd International Conference on Biomedical Engineering and Informatics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Detection of the Pulse Waveform Characteristic Points by Wavelet Transform Using Multiscale Differential Operator\",\"authors\":\"Qun Wang, Zhiwen Liu\",\"doi\":\"10.1109/BMEI.2009.5305400\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The pulse waveform characteristic point detection is important for non-invasively detecting cardiovascular parameters. A novel designed algorithm based on wavelet transform (WT) is developed. For some pulse waveforms, characteristic points exactly correspond to the zero-crossing of a wavelet with one vanishing moment, while the others incompletely correspond to. And characteristic points also correspond to the local extrema of a wavelet with two vanishing moment. So an algorithm combining a wavelet with one vanishing moment and another one with two vanishing moment is used to improve the detection rate of characteristic points. The results show that automatic identification of characteristics points has a high rate of accuracy.\",\"PeriodicalId\":6389,\"journal\":{\"name\":\"2009 2nd International Conference on Biomedical Engineering and Informatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 2nd International Conference on Biomedical Engineering and Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BMEI.2009.5305400\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 2nd International Conference on Biomedical Engineering and Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BMEI.2009.5305400","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

脉搏波形特征点检测是无创检测心血管参数的重要手段。提出了一种基于小波变换的新算法。对于某些脉冲波形,特征点完全对应于具有一个消失矩的小波的过零,而其他特征点则不完全对应于。特征点也对应于具有两个消失矩的小波的局部极值。为了提高特征点的检出率,提出了一种单消失矩小波和双消失矩小波相结合的算法。结果表明,特征点的自动识别具有较高的准确率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detection of the Pulse Waveform Characteristic Points by Wavelet Transform Using Multiscale Differential Operator
The pulse waveform characteristic point detection is important for non-invasively detecting cardiovascular parameters. A novel designed algorithm based on wavelet transform (WT) is developed. For some pulse waveforms, characteristic points exactly correspond to the zero-crossing of a wavelet with one vanishing moment, while the others incompletely correspond to. And characteristic points also correspond to the local extrema of a wavelet with two vanishing moment. So an algorithm combining a wavelet with one vanishing moment and another one with two vanishing moment is used to improve the detection rate of characteristic points. The results show that automatic identification of characteristics points has a high rate of accuracy.
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
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信