Saeed Zahran, Bayan Alrifai, Ahmad Diab, M. Khalil, C. Marque
{"title":"Separation and localization of EHG sources using tensor models","authors":"Saeed Zahran, Bayan Alrifai, Ahmad Diab, M. Khalil, C. Marque","doi":"10.1109/ICABME.2017.8167547","DOIUrl":null,"url":null,"abstract":"The use of the Electrohysterogram (EHG) for imaging the sources of the uterine electrical activity is a new and powerful diagnosis technique. However, its performance is limited as the uterus often demonstrates several simultaneously active regions and as EHGs present low signal-to-noise ratios. To overcome these problems, tensor-based preprocessing can be applied, which consists in constructing a space-time-frequency (STF) or space-time-wave-vector (STWV) tensor and decomposing it by using the Canonical Polyadic (CP) decomposition. In this paper, we present an algorithm for the accurate localization of extended sources based on the results of the tensor decomposition. Furthermore, we analyse its performance on realistic simulated data in comparison to conventional source localization algorithms.","PeriodicalId":426559,"journal":{"name":"2017 Fourth International Conference on Advances in Biomedical Engineering (ICABME)","volume":"11 1","pages":"0"},"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 Fourth International Conference on Advances in Biomedical Engineering (ICABME)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICABME.2017.8167547","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The use of the Electrohysterogram (EHG) for imaging the sources of the uterine electrical activity is a new and powerful diagnosis technique. However, its performance is limited as the uterus often demonstrates several simultaneously active regions and as EHGs present low signal-to-noise ratios. To overcome these problems, tensor-based preprocessing can be applied, which consists in constructing a space-time-frequency (STF) or space-time-wave-vector (STWV) tensor and decomposing it by using the Canonical Polyadic (CP) decomposition. In this paper, we present an algorithm for the accurate localization of extended sources based on the results of the tensor decomposition. Furthermore, we analyse its performance on realistic simulated data in comparison to conventional source localization algorithms.