Literature DB >> 17867347

Pulse morphology visualization and analysis with applications in cardiovascular pressure signals.

Tim Ellis1, James McNames, Mateo Aboy.   

Abstract

We present a new analysis and visualization method for studying the functional relationship between the pulse morphology of pressure signals and time or signal metrics such as heart rate, pulse pressure, and means of pressure signals, such as arterial blood pressure and central venous pressure. The pulse morphology is known to contain potentially useful clinical information, but it is difficult to study in the time domain without the aid of a tool such as the method we present here. The primary components of the method are established signal processing techniques, nonparametric regression, and an automatic beat detection algorithm. Some of the insights that can be gained from this are demonstrated through the analysis of intracranial pressure signals acquired from patients with traumatic brain injuries. The analysis indicates the point of transition from low-pressure morphology consisting of three distinct peaks to a high-pressure morphology consisting of a single peak. In addition, we demonstrate how the analysis can reveal distinctions in the relationship between morphology and several signal metrics for different patients.

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Mesh:

Year:  2007        PMID: 17867347     DOI: 10.1109/TBME.2007.892918

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


  9 in total

1.  A robust approach toward recognizing valid arterial-blood-pressure pulses.

Authors:  Shadnaz Asgari; Marvin Bergsneider; Xiao Hu
Journal:  IEEE Trans Inf Technol Biomed       Date:  2009-10-30

2.  Bayesian tracking of intracranial pressure signal morphology.

Authors:  Fabien Scalzo; Shadnaz Asgari; Sunghan Kim; Marvin Bergsneider; Xiao Hu
Journal:  Artif Intell Med       Date:  2011-10-02       Impact factor: 5.326

3.  Intracranial pressure pulse waveform correlates with aqueductal cerebrospinal fluid stroke volume.

Authors:  Robert Hamilton; Kevin Baldwin; Jennifer Fuller; Paul Vespa; Xiao Hu; Marvin Bergsneider
Journal:  J Appl Physiol (1985)       Date:  2012-09-20

4.  Forecasting ICP elevation based on prescient changes of intracranial pressure waveform morphology.

Authors:  Xiao Hu; Peng Xu; Shadnaz Asgari; Paul Vespa; Marvin Bergsneider
Journal:  IEEE Trans Biomed Eng       Date:  2010-05       Impact factor: 4.538

5.  Pattern recognition of overnight intracranial pressure slow waves using morphological features of intracranial pressure pulse.

Authors:  Magdalena Kasprowicz; Shadnaz Asgari; Marvin Bergsneider; Marek Czosnyka; Robert Hamilton; Xiao Hu
Journal:  J Neurosci Methods       Date:  2010-05-26       Impact factor: 2.390

6.  Lack of consistent intracranial pressure pulse morphological changes during episodes of microdialysis lactate/pyruvate ratio increase.

Authors:  Shadnaz Asgari; Paul Vespa; Marvin Bergsneider; Xiao Hu
Journal:  Physiol Meas       Date:  2011-09-09       Impact factor: 2.833

7.  Robust peak recognition in intracranial pressure signals.

Authors:  Fabien Scalzo; Shadnaz Asgari; Sunghan Kim; Marvin Bergsneider; Xiao Hu
Journal:  Biomed Eng Online       Date:  2010-10-19       Impact factor: 2.819

8.  Morphological clustering and analysis of continuous intracranial pressure.

Authors:  Xiao Hu; Peng Xu; Fabien Scalzo; Paul Vespa; Marvin Bergsneider
Journal:  IEEE Trans Biomed Eng       Date:  2008-11-07       Impact factor: 4.538

9.  Regression analysis for peak designation in pulsatile pressure signals.

Authors:  Fabien Scalzo; Peng Xu; Shadnaz Asgari; Marvin Bergsneider; Xiao Hu
Journal:  Med Biol Eng Comput       Date:  2009-07-04       Impact factor: 2.602

  9 in total

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