Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Prediction of decompression illness using bubble models

P Tikuisis1, K A Gault, R Y Nishi

  • 1Defence and Civil Institute of Environmental Medicine, North York, Canada.

Undersea & Hyperbaric Medicine : Journal of the Undersea and Hyperbaric Medical Society, Inc
|June 1, 1994
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Decompression sickness predictive models for unsafe human exposure.

Undersea & hyperbaric medicine : journal of the Undersea and Hyperbaric Medical Society, Inc·2013
Same author

Relationship between two different functions derived from diffusion-based decompression theory.

Undersea & hyperbaric medicine : journal of the Undersea and Hyperbaric Medical Society, Inc·2006
Same author

Selection of military survival gears using thermal manikin and computer survival model data.

European journal of applied physiology·2004
Same author

Effect of caffeine on target detection and rifle marksmanship.

Ergonomics·2003
Same author

Using animal data to improve prediction of human decompression risk following air-saturation dives.

Journal of applied physiology (Bethesda, Md. : 1985)·2002
Same author

Shivering endurance and fatigue during cold water immersion in humans.

European journal of applied physiology·2002
Same journal

Side Effects of Hyperbaric Oxygen Therapy.

Undersea & hyperbaric medicine : journal of the Undersea and Hyperbaric Medical Society, Inc·2026
Same journal

Avascular Necrosis (Aseptic Osteonecrosis).

Undersea & hyperbaric medicine : journal of the Undersea and Hyperbaric Medical Society, Inc·2026
Same journal

Adjunctive Hyperbaric Oxygen in the Treatment of Thermal Burns.

Undersea & hyperbaric medicine : journal of the Undersea and Hyperbaric Medical Society, Inc·2026
Same journal

Principles for the Design, Validation, and Acceptance of Decompression Procedures.

Undersea & hyperbaric medicine : journal of the Undersea and Hyperbaric Medical Society, Inc·2026
Same journal

A Non-Invasive Gas Exchange Monitor To Assess Swimming-Induced Pulmonary Edema.

Undersea & hyperbaric medicine : journal of the Undersea and Hyperbaric Medical Society, Inc·2026
Same journal

Dive Injury and Jellyfish Sting Case Study.

Undersea & hyperbaric medicine : journal of the Undersea and Hyperbaric Medical Society, Inc·2026
See all related articles

This study modeled bubble formation in divers to understand decompression illness (DCI). The equilibrium model best predicted DCI risk, suggesting bubble radius to the fourth power (R4) is a key factor.

Area of Science:

  • Physiology
  • Biophysics
  • Diving Medicine

Background:

  • Decompression illness (DCI) is a risk in diving, caused by bubble formation.
  • Understanding bubble dynamics is crucial for predicting and preventing DCI.

Purpose of the Study:

  • To apply maximum likelihood methods to bubble formation and evolution models for DCI risk assessment.
  • To compare equilibrium and non-equilibrium gas kinetic models under finite tissue volume constraints.

Main Methods:

  • Tested equilibrium (leq) and non-equilibrium (neq) gas kinetic models, plus a diffusivity-based model (vl).
  • Incorporated parameters like surface tension, gas exchange rate, solubility, and tissue time constant.
  • Analyzed 2,023 dives with 97 DCI and 27 marginal symptom occurrences.

Related Experiment Videos

Main Results:

  • The non-equilibrium (neq) and diffusivity (vl) models suggested a specific tissue perfusion rate for bubble formation.
  • The equilibrium model (leq) with risk based on bubble radius to the fourth power (R4) provided the best fit for a single compartment.
  • An estimated time constant of 95.6 +/- 9.8 min was found for the best-fit model.

Conclusions:

  • Bubble formation and evolution models, particularly the equilibrium model with R4 risk, can effectively predict DCI.
  • Identified key parameters influencing DCI risk, aiding in safer diving practices.