Peng Xu, Shaozhi Wu, S. Asgari, M. Kasprowicz, M. Bergsneider, Xiao Hu
{"title":"Comparison of Different Approaches to ICP Dominated Pulse Extraction","authors":"Peng Xu, Shaozhi Wu, S. Asgari, M. Kasprowicz, M. Bergsneider, Xiao Hu","doi":"10.1109/ICBBE.2009.5162539","DOIUrl":null,"url":null,"abstract":"Changes of ICP waveform morphology are characterized with different patients' states like hypertension, hydrocephalus and traumatic brain injury etc. Morphological clustering and analysis of ICP pulse (MOCAIP) approach is recently developed to extract ICP morphology feature, in which hierarchical clustering is used to extract the dominated pulse. In this paper, we evaluate the feasibility of using principle component analysis (PCA) and independent component analysis (ICA) to extract dominated pulse. The comparative study among clustering, PCA and ICP based approaches shows that PCA approach may be an alternative of clustering approach to extract dominated pulse in a faster fashion when dataset is of large size.","PeriodicalId":6430,"journal":{"name":"2009 3rd International Conference on Bioinformatics and Biomedical Engineering","volume":"11 1","pages":"1-4"},"PeriodicalIF":0.0000,"publicationDate":"2009-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 3rd International Conference on Bioinformatics and Biomedical Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICBBE.2009.5162539","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
Changes of ICP waveform morphology are characterized with different patients' states like hypertension, hydrocephalus and traumatic brain injury etc. Morphological clustering and analysis of ICP pulse (MOCAIP) approach is recently developed to extract ICP morphology feature, in which hierarchical clustering is used to extract the dominated pulse. In this paper, we evaluate the feasibility of using principle component analysis (PCA) and independent component analysis (ICA) to extract dominated pulse. The comparative study among clustering, PCA and ICP based approaches shows that PCA approach may be an alternative of clustering approach to extract dominated pulse in a faster fashion when dataset is of large size.