DocumentCode
6937
Title
A New Approach for Investigating Intracranial Pressure Signal: Filtering and Morphological Features Extraction from Continuous Recording
Author
Calisto, A. ; Galeano, M. ; Serrano, S. ; Calisto, A. ; Azzerboni, Bruno
Author_Institution
Dept. of Electron. Eng., Ind. Chem. & Eng., Univ. of Messina, Messina, Italy
Volume
60
Issue
3
fYear
2013
fDate
Mar-13
Firstpage
830
Lastpage
837
Abstract
Nowadays, the Intracranial Pressure (ICP) monitoring has become the most common method of investigation for both traumatic and chronic neural pathologies. ICP signals are typically triphasic, that is, in a single waveform, three subpeaks can be identified. This work outlines a new algorithm to identify subpeaks from the ICP recordings and to extract a number of 20 meaningful parameter trends. The validity of the implemented method has been proved through a comparison between the automatic subpeaks identification by the algorithm and the manually marked subpeaks by a neurosurgeon. The automatic marking system has identified subpeaks for the 63.74% (mean value) of pulse waves, providing the position and amplitude of each identified subpeak within a tolerance of ±7 samples. This automatic system provides a feature set to be used by classification software to obtain more precise and easier diagnosis in all those cases that involve brain damages or diseases.
Keywords
brain; classification; diseases; feature extraction; medical signal processing; neurophysiology; patient diagnosis; patient monitoring; ICP recordings; ICP signals; automatic subpeak identification; automatic system; brain damages; chronic neural pathologies; classification software; continuous recording; diseases; filtering features extraction; intracranial pressure monitoring; intracranial pressure signal; morphological features extraction; neurosurgeon; patient diagnosis; pulse wave mean value; single waveform; subpeak amplitude; subpeak position; traumatic pathologies; triphasic signal; Feature extraction; Filtering algorithms; Finite impulse response filter; Iterative closest point algorithm; Noise; Signal processing algorithms; Biomedical monitoring; Computer aided diagnosis; Hypertension; Intracranial pressure (ICP) sensors; Medical signal detection; signal processing; transducers; Adult; Aged; Algorithms; Diagnosis, Computer-Assisted; Female; Humans; Hydrocephalus, Normal Pressure; Intracranial Pressure; Male; Middle Aged; Monitoring, Physiologic; Reproducibility of Results; Signal Processing, Computer-Assisted; Spinal Puncture; Transducers;
fLanguage
English
Journal_Title
Biomedical Engineering, IEEE Transactions on
Publisher
ieee
ISSN
0018-9294
Type
jour
DOI
10.1109/TBME.2012.2191550
Filename
6172560
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