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Related Experiment Video

Updated: Jun 21, 2026

Translaminar Autonomous System Model for the Modulation of Intraocular and Intracranial Pressure in Human Donor Posterior Segments

Translaminar Autonomous System Model for the Modulation of Intraocular and Intracranial Pressure in Human Donor Posterior Segments

Published on: April 24, 2020

Accurate intraocular pressure prediction from applanation response data using genetic algorithm and neural networks.

Jamshid Ghaboussi¹, Tae-Hyun Kwon, David A Pecknold

¹Department of Civil and Environmental Engineering, University of Illinois at Urban-Champaign, Urbana, IL 61801, USA.

Journal of Biomechanics

|August 8, 2009

Summary

Accurate intraocular pressure (IOP) measurement requires considering corneal elasticity, not just thickness. This study introduces a computational method using a modified tonometer for precise IOP and corneal property determination.

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Trabecular Meshwork Response to Pressure Elevation in the Living Human Eye

Trabecular Meshwork Response to Pressure Elevation in the Living Human Eye

Published on: June 20, 2015

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Last Updated: Jun 21, 2026

Translaminar Autonomous System Model for the Modulation of Intraocular and Intracranial Pressure in Human Donor Posterior Segments

Translaminar Autonomous System Model for the Modulation of Intraocular and Intracranial Pressure in Human Donor Posterior Segments

Published on: April 24, 2020

Trabecular Meshwork Response to Pressure Elevation in the Living Human Eye

Trabecular Meshwork Response to Pressure Elevation in the Living Human Eye

Published on: June 20, 2015

Area of Science:

Ophthalmology
Biomedical Engineering
Computational Mechanics

Background:

Goldmann applanation tonometry is the standard for intraocular pressure (IOP) measurement.
However, it often yields inaccurate IOP readings due to its failure to account for individual corneal elastic stiffness.
Accurate IOP assessment necessitates considering central corneal thickness (CCT) and other corneal biomechanical factors.

Purpose of the Study:

To investigate a computational method for accurate and reliable IOP determination.
To develop a technique that accounts for corneal biomechanical properties beyond CCT.
To assess the feasibility of determining CCT and corneal material properties simultaneously.

Main Methods:

A modified applanation tonometer was employed.
A computational approach combined a genetic algorithm and a neural network.
This method matched clinical applanation force-displacement data with nonlinear finite element simulation results.

Main Results:

The proposed method accurately determines IOP by incorporating corneal biomechanics.
It simultaneously provides estimations of CCT and corneal material properties.
The method demonstrated computational efficiency, suitable for clinical application.

Conclusions:

A novel computational method enhances IOP measurement accuracy by integrating corneal biomechanical factors.
This approach offers a more comprehensive assessment of corneal properties.
The method shows promise for improved clinical diagnosis and management of eye conditions.