DocumentCode :
2480833
Title :
Classification of morphological features extracted from intracranial pressure recordings in the diagnosis of Normal Pressure Hydrocephalus (NPH)
Author :
Galeano, M. ; Calisto, A. ; Bramanti, A. ; Angileri, F. ; Campobello, G. ; Serrano, S. ; Azzerboni, B.
Author_Institution :
Dept. of Matter Phys. & Electron. Eng., Univ. of Messina, Messina, Italy
fYear :
2011
fDate :
Aug. 30 2011-Sept. 3 2011
Firstpage :
2768
Lastpage :
2771
Abstract :
The intracranial pressure (ICP) monitoring is a common procedure in neuro-intensive care for pathologies such traumatic brain injuries or hemorrhages, but also for chronic ones as the Normal Pressure Hydrocephalus (NPH). The only available treatment for NPH is the surgical implantation of a shunt with the aim of routing cerebrospinal fluid (CSF) away from the brain to another part of the body. In this study, using the classification software WEKA, an intensive investigation of ICP signals has been conducted. In particular we studied 14 ICP recordings of different patients who underwent an infusion test, with the aim of investigating the presence of NPH through the ICP recording. More precisely, 20 morphological features are extracted from the ICP pulsed wave, the trend have been computed and, for each one, 9 statistical functions determined. The 180 features have been selected and passed for the classification. The results obtained shows how, among the 14 patients, a number of 12 out of 14 (85.7%) have been correctly classified, looking at just 3 features. In particular 8 out of 9 not-NPH-affected patients were correctly identified (88.89%) while 4 out of 5 NPH-affected patients were correctly identified (80%).
Keywords :
brain; feature extraction; medical signal processing; patient diagnosis; patient monitoring; signal classification; statistical analysis; surgery; ICP pulsed wave; ICP signal; NPH diagnosis; brain; cerebrospinal fluid; classification software WEKA; infusion test; intracranial pressure monitoring; intracranial pressure recording; morphological feature extraction; neurointensive care; normal pressure hydrocephalus diagnosis; shunt; statistical function; surgical implantation; Data mining; Databases; Feature extraction; Fluids; Iterative closest point algorithm; Pathology; Software; Algorithms; Humans; Hydrocephalus, Normal Pressure; Intracranial Pressure;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE
Conference_Location :
Boston, MA
ISSN :
1557-170X
Print_ISBN :
978-1-4244-4121-1
Electronic_ISBN :
1557-170X
Type :
conf
DOI :
10.1109/IEMBS.2011.6090758
Filename :
6090758
Link To Document :
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