Literature DB >> 27733932

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

Tricia Adjei1, Daniel Abásolo2, David Santamarta3.   

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 nonlinear 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 with 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 Letter suggests that advanced signal processing of ICP signals with LZ complexity can help characterise different types of hydrocephalus in more detail.

Entities:  

Keywords:  Lempel–Ziv complexity; SH; brain; enlarged cerebral ventricles; iNPH; idiopathic normal pressure hydrocephalus patients; infusion studies; intracranial pressure signals; medical disorders; medical signal processing; nonlinear signal processing; secondary normal pressure hydrocephalus patients

Year:  2016        PMID: 27733932      PMCID: PMC5047286          DOI: 10.1049/htl.2016.0018

Source DB:  PubMed          Journal:  Healthc Technol Lett        ISSN: 2053-3713


  8 in total

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Authors:  María García; Jesús Poza; David Santamarta; Daniel Abásolo; Patricia Barrio; Roberto Hornero
Journal:  Med Eng Phys       Date:  2013-05-09       Impact factor: 2.242

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Authors:  Cheng-Wei Lu; Marek Czosnyka; Jiann-Shing Shieh; Anna Smielewska; John D Pickard; Peter Smielewski
Journal:  Brain       Date:  2012-06-25       Impact factor: 13.501

  8 in total

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