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Simulated Workflow Feasibility Evaluation of a Web-Based Periorbital Measurement Platform: Development and Usability
George R Nahass1,2, Jacob van der Ende3, Sasha Hubschman2
1Department of Biomedical Engineering, University of Illinois Chicago, Chicago, IL, United States.
JMIR Human Factors
|April 30, 2026
Summary
Gorbit, an AI-powered app, streamlines periorbital measurements for eyelid condition research. It successfully captured and analyzed images across devices in simulated tests, proving its workflow feasibility.
Area of Science:
- Ophthalmology
- Medical Imaging
- Artificial Intelligence
Background:
- Periorbital measurements are crucial for diagnosing and managing eyelid disorders like ptosis.
- Current automated measurement tools lack integrated data capture and management infrastructure for research.
Purpose of the Study:
- To develop and evaluate Glorbit, a browser-based application for automated periorbital distance measurement using AI.
- To assess the end-to-end workflow feasibility of Glorbit under simulated, operator-run conditions.
Main Methods:
- Gorbit integrates a DeepLabV3 segmentation model with Google Cloud storage and Firebase authentication.
- The application supports local preprocessing, cloud upload, and metadata entry.
- The complete workflow was tested in simulated, operator-run sessions, followed by participant surveys.
Main Results:
- Gorbit ran successfully on various platforms (laptops, tablets, mobile phones) and browsers.
- The application completed all workflow steps in simulated sessions with 15 volunteers.
- The AI model produced outputs for all images, with an average session duration of 101.7 seconds and high user satisfaction.
Conclusions:
- Gorbit is a cross-platform application enabling structured periorbital image capture and automated analysis.
- The platform demonstrated successful workflow execution across devices in simulated testing.
- Gorbit shows technical feasibility as a research data collection framework for future evaluations.
