使用CANDECOMP / PARAFAC算法分解心血管信号张量

F. N. Almirantearena
{"title":"使用CANDECOMP / PARAFAC算法分解心血管信号张量","authors":"F. N. Almirantearena","doi":"10.1109/CISP-BMEI.2017.8302217","DOIUrl":null,"url":null,"abstract":"In the processing of biological signals of the electrocardiogram (ECG) and Arterial Diameter Variation (ADV) there are several methods for the extraction of cardiovascular event characteristics. In this case, the canonical polyadic decomposition of CANDECOMP/PARAFAC (CP) tensors is used in the processing of the mixed signals of ECG-ADV; the ECG-ADV signals are extracted from each patient simultaneously and the detection quality of the ECG complex is verified. To do this, the ECG complex and the systolic wave of the ADV wave are aligned with Gaussian noise, and then the tensors were constructed for both signals. Five algorithms of CP were applied and the quality of the factorization of each one of the algorithms was checked with four indices. Both signals were shown to be non-collinear, and the algorithms that have the minimum number of iterations at the convergence were determined.","PeriodicalId":6474,"journal":{"name":"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","volume":"6 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Decomposition of tensors of cardio-vascular signals using CANDECOMP / PARAFAC algorithms\",\"authors\":\"F. N. Almirantearena\",\"doi\":\"10.1109/CISP-BMEI.2017.8302217\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In the processing of biological signals of the electrocardiogram (ECG) and Arterial Diameter Variation (ADV) there are several methods for the extraction of cardiovascular event characteristics. In this case, the canonical polyadic decomposition of CANDECOMP/PARAFAC (CP) tensors is used in the processing of the mixed signals of ECG-ADV; the ECG-ADV signals are extracted from each patient simultaneously and the detection quality of the ECG complex is verified. To do this, the ECG complex and the systolic wave of the ADV wave are aligned with Gaussian noise, and then the tensors were constructed for both signals. Five algorithms of CP were applied and the quality of the factorization of each one of the algorithms was checked with four indices. Both signals were shown to be non-collinear, and the algorithms that have the minimum number of iterations at the convergence were determined.\",\"PeriodicalId\":6474,\"journal\":{\"name\":\"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)\",\"volume\":\"6 1\",\"pages\":\"1-6\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CISP-BMEI.2017.8302217\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP-BMEI.2017.8302217","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

在心电图(ECG)和动脉直径变化(ADV)的生物信号处理中,有几种提取心血管事件特征的方法。在这种情况下,使用CANDECOMP/PARAFAC (CP)张量的正则多进分解来处理ECG-ADV的混合信号;同时提取每个患者的ECG- adv信号,验证心电图复合体的检测质量。为此,将心电复合体和ADV波的收缩期波与高斯噪声对齐,然后对这两个信号分别构造张量。应用了5种CP算法,并用4个指标检验了每种算法的分解质量。证明了两个信号都是非共线的,并确定了收敛处迭代次数最少的算法。
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
Decomposition of tensors of cardio-vascular signals using CANDECOMP / PARAFAC algorithms
In the processing of biological signals of the electrocardiogram (ECG) and Arterial Diameter Variation (ADV) there are several methods for the extraction of cardiovascular event characteristics. In this case, the canonical polyadic decomposition of CANDECOMP/PARAFAC (CP) tensors is used in the processing of the mixed signals of ECG-ADV; the ECG-ADV signals are extracted from each patient simultaneously and the detection quality of the ECG complex is verified. To do this, the ECG complex and the systolic wave of the ADV wave are aligned with Gaussian noise, and then the tensors were constructed for both signals. Five algorithms of CP were applied and the quality of the factorization of each one of the algorithms was checked with four indices. Both signals were shown to be non-collinear, and the algorithms that have the minimum number of iterations at the convergence were determined.
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
Polarization Characterization and Evaluation of Healing Process of the Damaged-skin Applied with Chitosan and Silicone Hydrogel Applicator Design and Implementation of OpenDayLight Manager Application Extraction of cutting plans in craniosynostosis using convolutional neural networks Evaluation of Flight Test Data Quality Based on Rough Set Theory Radar Emitter Type Identification Effect Based On Different Structural Deep Feedforward Networks
×
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