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Updated: Mar 22, 2026

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Quantification of Oculomotor Responses and Accommodation Through Instrumentation and Analysis Toolboxes
Published on: March 3, 2023
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Predicting Accommodative Response Using Paraxial Schematic Eye Models.
Viswanathan Ramasubramanian1, Adrian Glasser
1*PhD The College of Optometry, University of Houston, Houston, Texas (all authors).
Summary
Paraxial schematic eyes (SE) accurately predict accommodative optical response (AOR) with a 0.50D standard deviation in young and pre-presbyopic individuals. This method incorporates all ocular biometric parameters for improved predictive accuracy.
Area of Science:
- Ophthalmology
- Biomedical Engineering
- Optometry
Background:
- Previous ultrasound biomicroscopy (UBM) studies established linear relationships for predicting accommodative optical response (AOR) from biometric changes.
- These predictions had a standard deviation below 0.55D in young and pre-presbyopic populations.
Purpose of the Study:
- To construct paraxial schematic eyes (SE) using measured accommodative ocular biometry.
- To determine if these SE models improve the prediction of AOR compared to previous methods.
Main Methods:
- Ocular biometry parameters were measured using OCT, A-scan, and UBM in 48 subjects (24 young, 24 pre-presbyopic).
- Individual paraxial SEs were constructed for each subject using three lens equivalent refractive index methods.
- Calculated AOR from individual SEs were compared against Grand Seiko (GS) autorefractor measurements.
Main Results:
- A linear relationship was found between SE-calculated and GS-measured AOR (young: r=0.86; pre-presbyopic: r=0.55).
- The mean absolute difference in AOR between GS and individual SEs was 0.50D for both young and pre-presbyopic subjects.
- Average SEs showed a larger mean absolute difference (0.77D for young, 0.51D for pre-presbyopic).
Conclusions:
- Individual paraxial SEs predict AOR with a standard deviation of 0.50D in both young and pre-presbyopic populations.
- This predictive model, while marginally better than linear regressions, comprehensively integrates all ocular biometric parameters.
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