A method for the automated detection of venous gas bubbles in humans using empirical mode decomposition
Journal
Annals of Biomedical Engineering
Journal Volume
33
Journal Issue
10
Pages
1411-1421
Date Issued
2005
Author(s)
Abstract
Doppler ultrasound signals are widely used to grade the quantity of circulating venous bubbles in divers. Current techniques rely on trained observers, making the grading process both time-consuming and subjective. The automated detection of bubbles, however, is confounded by the presence of other signals, primarily those arising from blood motion. Empirical Mode Decomposition was used here to calculate the intrinsic mode functions (IMFs) of a number of Doppler ultrasound signals from recreational divers, post-decompression. The IMFs provide a basis set for signal decomposition, each IMF corresponding to a different timescale in the signal. Each signal was found to comprise approximately 20 IMFs: the precise number being dependent upon the nature of the signal. A method is presented to detect bubbles using the IMF; features are first identified in the individual heart cycles, these having been previously determined using a robust peak detection method, by examining deviations from the ensemble averaged IMF. Bubbles are then identified as features appearing in more than one IMF, with significant energy in the original signal. This method has been applied to a subset of the available database and appears to perform with good sensitivity even when the signal has variable signal strength. ? 2005 Biomedical Engineering Society.
Subjects
Automation
Bubbles (in fluids)
Doppler effect
Ultrasonics
Decompression sickness
Doppler ultrasound
Hilbert-Huang transform
Biomedical engineering
air embolism
article
artificial intelligence
automated pattern recognition
blood
computer assisted diagnosis
decompression sickness
diving
Doppler flowmetry
echography
gas
human
metabolism
methodology
reproducibility
sensitivity and specificity
vein
Artificial Intelligence
Decompression Sickness
Diving
Embolism, Air
Gases
Humans
Image Interpretation, Computer-Assisted
Pattern Recognition, Automated
Reproducibility of Results
Sensitivity and Specificity
Ultrasonography, Doppler
Veins
Type
journal article