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Characterisation of the complexity of intracranial pressure signals measured from idiopathic and secondary normal pressure hydrocephalus patients

Adjei, T, Abasolo, D and Santamarta, D (2016) Characterisation of the complexity of intracranial pressure signals measured from idiopathic and secondary normal pressure hydrocephalus patients Healthcare Technology Letters, 3 (3). pp. 226-229.

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Abstract

Hydrocephalus is a condition characterised by enlarged cerebral ventricles, which in turn affects intracranial pressure (ICP); however, the mechanisms regulating ICP are not fully understood. A non-linear signal processing approach was applied to ICP signals measured during infusion studies from patients with two forms of hydrocephalus, in a bid to compare the differences. This is the first study of its kind. The two forms of hydrocephalus were idiopathic normal pressure hydrocephalus (iNPH) and secondary normal pressure hydrocephalus (SH). Following infusion tests, the Lempel-Ziv (LZ) complexity was calculated from the iNPH and SH ICP signals. The LZ complexity values were averaged for the baseline, infusion, plateau and recovery stages of the tests. It was found that as the ICP increased from basal levels, the LZ complexities decreased, reaching their lowest during the plateau stage. However, the complexities computed from the SH ICP signals decreased to a lesser extent when compared to the iNPH ICP signals. Furthermore, statistically significant differences were found between the plateau and recovery stage complexities when comparing the iNPH and SH results (p << 0.05). This study suggests that advanced signal processing of ICP signals with LZ complexity can help characterise different types of hydrocephalus in more detail.

Item Type: Article
Subjects : Mechanical Engineering Science
Divisions : Faculty of Engineering and Physical Sciences > Mechanical Engineering Sciences
Authors :
AuthorsEmailORCID
Adjei, TUNSPECIFIEDUNSPECIFIED
Abasolo, DUNSPECIFIEDUNSPECIFIED
Santamarta, DUNSPECIFIEDUNSPECIFIED
Date : 5 July 2016
Funders : EPSRC
Identification Number : 10.1049/htl.2016.0018
Copyright Disclaimer : © The Institution of Engineering and Technology. This paper is a postprint of a paper submitted to and accepted for publication in Healthcare Technology Letters and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at IET Digital Library.
Related URLs :
Depositing User : Symplectic Elements
Date Deposited : 16 Aug 2016 11:53
Last Modified : 29 Nov 2016 18:15
URI: http://epubs.surrey.ac.uk/id/eprint/811719

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