{"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}
引用次数: 3
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.