A Semi-Automatic Feature Detection Algorithm for Hemodynamic Signals using Curvature-Based Feature Extraction

Specific features of hemodynamic signals are invaluable for elucidating ventricular and vascular function. A semi-automatic algorithm is presented that enables accurate detection of any feature in any hemodynamic signal, using feature extraction from local maxima and minima in signal curvature. A pa...

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Bibliographic Details
Published in2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Vol. 2007; pp. 1691 - 1694
Main Authors Mynard, J.P., Penny, D.J., Smolich, J.J.
Format Conference Proceeding Journal Article
LanguageEnglish
Published United States IEEE 01.01.2007
Subjects
Algorithm design and analysis
Algorithms
Aorta - pathology
Australia
Automatic Data Processing
Automation
Computer vision
Computers
Detection algorithms
Equipment Design
Feature extraction
Frequency
Graphical user interfaces
Heart
Hemodynamics
Humans
Image Processing, Computer-Assisted
Models, Theoretical
Pattern Recognition, Automated
Pressure
Signal analysis
Signal Processing, Computer-Assisted
Software
Time Factors
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Summary:Specific features of hemodynamic signals are invaluable for elucidating ventricular and vascular function. A semi-automatic algorithm is presented that enables accurate detection of any feature in any hemodynamic signal, using feature extraction from local maxima and minima in signal curvature. A particular feature is selected manually in the first beat and then detected automatically in subsequent beats.
ISBN:9781424407873
1424407877
ISSN:1094-687X
1557-170X
1558-4615
DOI:10.1109/IEMBS.2007.4352634