NDLI: Multivariate analysis of intracranial pressure (ICP) signal using principal component analysis

Content Provider	IEEE Xplore Digital Library
Author	Al-Zubi, N. Momani, L. Al-kharabsheh, A. Al-Nuaimy, W.
Copyright Year	2009
Description	Author affiliation: Electrical Engineering and Electronics Department, University of Liverpool, Brownlow Hill, Liverpool, UK (Al-Zubi, N.; Momani, L.; Al-kharabsheh, A.; Al-Nuaimy, W.)
Abstract	The diagnosis and treatment of hydrocephalus and other neurological disorders often involve the acquisition and analysis of large amount of intracranial pressure (ICP) signal. Although the analysis and subsequent interpretation of this data is an essential part of the clinical management of the disorders, it is typically done manually by a trained clinician, and the difficulty in interpreting some of the features of this complex time series can sometimes lead to issues of subjectivity and reliability. This paper presents a method for the quantitative analysis of this data using a multivariate approach based on principal component analysis, with the aim of optimising symptom diagnosis, patient characterisation and treatment simulation and personalisation. In this method, 10 features are extracted from the ICP signal and principal components that represent these features are defined and analysed. Results from ICP traces of 40 patients show that the chosen features have relevant information about the ICP signal and can be represented with a few components of the PCA (approximately 91% of the total variance of the data is represented by the first four components of the PCA) and that these components can be helpful in characterising subgroups in the patient population that would otherwise not have been apparent. The introduction of supplementaty (non-ICP) variables has offered insight into additional groupings and relationships which may prove to be a fruitful avenue for exploration.
Starting Page	4670
Ending Page	4673
File Size	553428
Page Count	4
File Format	PDF
ISBN	9781424432967
ISSN	1557170X
DOI	10.1109/IEMBS.2009.5334225
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-03
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Signal analysis Cranial pressure Principal component analysis Time series analysis Data analysis Optimization methods Medical treatment Analytical models Feature extraction Data mining
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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