Literature DB >> 22453602

A new approach for investigating intracranial pressure signal: filtering and morphological features extraction from continuous recording.

Andrea Calisto1, Massimiliano Galeano, Salvatore Serrano, Amedeo Calisto, Bruno Azzerboni.   

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.

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Mesh:

Year:  2012        PMID: 22453602     DOI: 10.1109/TBME.2012.2191550

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  4 in total

1.  An active learning framework for enhancing identification of non-artifactual intracranial pressure waveforms.

Authors:  Murad Megjhani; Ayham Alkhachroum; Kalijah Terilli; Jenna Ford; Clio Rubinos; Julie Kromm; Brendan K Wallace; E Sander Connolly; David Roh; Sachin Agarwal; Jan Claassen; Raghav Padmanabhan; Xiao Hu; Soojin Park
Journal:  Physiol Meas       Date:  2019-01-18       Impact factor: 2.833

2.  Compliance of the cerebrospinal space: comparison of three methods.

Authors:  Agnieszka Kazimierska; Magdalena Kasprowicz; Marek Czosnyka; Michał M Placek; Olivier Baledent; Peter Smielewski; Zofia Czosnyka
Journal:  Acta Neurochir (Wien)       Date:  2021-04-14       Impact factor: 2.216

3.  Patient-adaptable intracranial pressure morphology analysis using a probabilistic model-based approach.

Authors:  Paria Rashidinejad; Xiao Hu; Stuart Russell
Journal:  Physiol Meas       Date:  2020-11-06       Impact factor: 2.833

Review 4.  Automated Detection and Screening of Traumatic Brain Injury (TBI) Using Computed Tomography Images: A Comprehensive Review and Future Perspectives.

Authors:  Vidhya V; Anjan Gudigar; U Raghavendra; Ajay Hegde; Girish R Menon; Filippo Molinari; Edward J Ciaccio; U Rajendra Acharya
Journal:  Int J Environ Res Public Health       Date:  2021-06-16       Impact factor: 3.390

  4 in total

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