ICP主导脉冲提取不同方法的比较

Peng Xu, Shaozhi Wu, S. Asgari, M. Kasprowicz, M. Bergsneider, Xiao Hu
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引用次数: 1

摘要

颅内压波形形态变化具有高血压、脑积水、颅脑外伤等不同状态的特点。ICP脉冲形态聚类与分析(MOCAIP)方法是近年来发展起来的ICP形态特征提取方法,该方法采用分层聚类的方法提取主导脉冲。本文对主成分分析(PCA)和独立成分分析(ICA)提取支配脉冲的可行性进行了评价。通过对聚类方法、PCA方法和ICP方法的比较研究表明,当数据集规模较大时,PCA方法可以替代聚类方法更快地提取主导脉冲。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparison of Different Approaches to ICP Dominated Pulse Extraction
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.
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