Radar-based Measurement of Pulse Wave using Fast Physiological Component Analysis

T. Sakamoto, Junya Suzuguchi
{"title":"Radar-based Measurement of Pulse Wave using Fast Physiological Component Analysis","authors":"T. Sakamoto, Junya Suzuguchi","doi":"10.1109/iWAT54881.2022.9811091","DOIUrl":null,"url":null,"abstract":"This study proposes a fast blind signal separation technique for human arterial pulse wave propagation measurement. One of the authors previously developed a blind signal separation method called physiological component analysis that uses mathematical modeling of the measured physiological signals, including the pulse wave propagation, and this method improves the signal separation accuracy when applied to array signal processing. Physiological component analysis, however, is known to require long computation times because it is based on high-dimensional global optimization. In this paper, we propose a method to reduce the dimensionality of the decision variables for the optimization process that uses the Schelkunoff polynomial method. Using this dimension reduction technique, we propose a new algorithm, called fast physiological component analysis, and the performance of this algorithm is evaluated using numerical simulations.","PeriodicalId":106416,"journal":{"name":"2022 International Workshop on Antenna Technology (iWAT)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Workshop on Antenna Technology (iWAT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iWAT54881.2022.9811091","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

This study proposes a fast blind signal separation technique for human arterial pulse wave propagation measurement. One of the authors previously developed a blind signal separation method called physiological component analysis that uses mathematical modeling of the measured physiological signals, including the pulse wave propagation, and this method improves the signal separation accuracy when applied to array signal processing. Physiological component analysis, however, is known to require long computation times because it is based on high-dimensional global optimization. In this paper, we propose a method to reduce the dimensionality of the decision variables for the optimization process that uses the Schelkunoff polynomial method. Using this dimension reduction technique, we propose a new algorithm, called fast physiological component analysis, and the performance of this algorithm is evaluated using numerical simulations.
基于快速生理成分分析的脉冲波雷达测量
提出了一种用于人体动脉脉搏波传播测量的快速盲信号分离技术。其中一位作者先前开发了一种盲信号分离方法,称为生理成分分析,该方法对测量的生理信号进行数学建模,包括脉冲波的传播,该方法在应用于阵列信号处理时提高了信号分离的精度。然而,由于生理成分分析是基于高维全局优化的,因此需要很长的计算时间。本文提出了一种利用舍尔库诺夫多项式方法对优化过程中的决策变量进行降维的方法。利用这种降维技术,我们提出了一种新的快速生理成分分析算法,并通过数值模拟对该算法的性能进行了评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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