Title :
A Semi-Automatic Feature Detection Algorithm for Hemodynamic Signals using Curvature-Based Feature Extraction
Author :
Mynard, J.P. ; Penny, D.J. ; Smolich, J.J.
Author_Institution :
Murdoch Children´s Res. Inst., Melbourne
Abstract :
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.
Keywords :
cardiology; feature extraction; haemodynamics; medical signal detection; medical signal processing; feature detection; feature extraction; hemodynamic signals; semiautomatic algorithm; signal curvature; vascular function; ventricular function; Algorithm design and analysis; Australia; Computer vision; Detection algorithms; Feature extraction; Frequency; Graphical user interfaces; Heart; Hemodynamics; Signal analysis; Algorithms; Aorta; Automatic Data Processing; Automation; Computers; Equipment Design; Hemodynamics; Humans; Image Processing, Computer-Assisted; Models, Theoretical; Pattern Recognition, Automated; Pressure; Signal Processing, Computer-Assisted; Software; Time Factors;
Conference_Titel :
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE
Conference_Location :
Lyon
Print_ISBN :
978-1-4244-0787-3
DOI :
10.1109/IEMBS.2007.4352634
